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Natural Language Processing (NLP) & Text Mining Tutorial Using NLTK | NLP Training | Edureka
 
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** NLP Using Python: - https://www.edureka.co/python-natural-language-processing-course ** This Edureka video will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP. You will also learn about the different steps involved in processing the human language like Tokenization, Stemming, Lemmatization and much more along with a demo on each one of the topics. The following topics covered in this video : 1. The Evolution of Human Language 2. What is Text Mining? 3. What is Natural Language Processing? 4. Applications of NLP 5. NLP Components and Demo Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV --------------------------------------------------------------------------------------------------------- Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Instagram: https://www.instagram.com/edureka_learning/ --------------------------------------------------------------------------------------------------------- - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Natural Language Processing using Python Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learnt content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics and Machine Learning have been discussed. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience. -------------------------- Who Should go for this course ? Edureka’s NLP Training is a good fit for the below professionals: From a college student having exposure to programming to a technical architect/lead in an organisation Developers aspiring to be a ‘Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Text Mining Techniques 'Python' professionals who want to design automatic predictive models on text data "This is apt for everyone” --------------------------------- Why Learn Natural Language Processing or NLP? Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users. NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data. --------------------------------- For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
Views: 52002 edureka!
Natural Language Processing in Python
 
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Alice Zhao https://pyohio.org/2018/schedule/presentation/38/ Natural language processing (NLP) is an exciting branch of artificial intelligence (AI) that allows machines to break down and understand human language. As a data scientist, I often use NLP techniques to interpret text data that I'm working with for my analysis. During this tutorial, I plan to walk through text pre-processing techniques, machine learning techniques and Python libraries for NLP. Text pre-processing techniques include tokenization, text normalization and data cleaning. Once in a standard format, various machine learning techniques can be applied to better understand the data. This includes using popular modeling techniques to classify emails as spam or not, or to score the sentiment of a tweet on Twitter. Newer, more complex techniques can also be used such as topic modeling, word embeddings or text generation with deep learning. We will walk through an example in Jupyter Notebook that goes through all of the steps of a text analysis project, using several NLP libraries in Python including NLTK, TextBlob, spaCy and gensim along with the standard machine learning libraries including pandas and scikit-learn. ## Setup Instructions [ https://github.com/adashofdata/nlp-in-python-tutorial](https://github.com/adashofdata/nlp-in-python-tutorial) === https://pyohio.org A FREE annual conference for anyone interested in Python in and around Ohio, the entire Midwest, maybe even the whole world.
Views: 29198 PyOhio
Natural Language Processing (NLP) Tutorial with Python & NLTK
 
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This video will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP. You will also learn about the different steps involved in processing the human language like Tokenization, Stemming, Lemmatization and more. Python, NLTK, & Jupyter Notebook are used to demonstrate the concepts. This tutorial was developed by Edureka. 🔗NLP Certification Training: https://goo.gl/kn2H8T 🔗Subscribe to the Edureka YouTube channel: https://www.youtube.com/user/edurekaIN 🔗Edureka Online Training: https://www.edureka.co/ -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://medium.freecodecamp.org And subscribe for new videos on technology every day: https://youtube.com/subscription_center?add_user=freecodecamp
Views: 20708 freeCodeCamp.org
Natural Language Processing With Python and NLTK p.1 Tokenizing words and Sentences
 
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Natural Language Processing is the task we give computers to read and understand (process) written text (natural language). By far, the most popular toolkit or API to do natural language processing is the Natural Language Toolkit for the Python programming language. The NLTK module comes packed full of everything from trained algorithms to identify parts of speech to unsupervised machine learning algorithms to help you train your own machine to understand a specific bit of text. NLTK also comes with a large corpora of data sets containing things like chat logs, movie reviews, journals, and much more! Bottom line, if you're going to be doing natural language processing, you should definitely look into NLTK! Playlist link: https://www.youtube.com/watch?v=FLZvOKSCkxY&list=PLQVvvaa0QuDf2JswnfiGkliBInZnIC4HL&index=1 sample code: http://pythonprogramming.net http://hkinsley.com https://twitter.com/sentdex http://sentdex.com http://seaofbtc.com
Views: 474506 sentdex
Natural Language Processing In 10 Minutes | NLP Tutorial For Beginners | NLP Training | Edureka
 
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** Natural Language Processing Using Python: https://www.edureka.co/python-natural-language-processing-course ** This Edureka video will provide you with a short and crisp description of NLP (Natural Language Processing) and Text Mining. You will also learn about the various applications of NLP in the industry. NLP Tutorial : https://www.youtube.com/watch?v=05ONoGfmKvA Subscribe to our channel to get video updates. Hit the subscribe button above. ------------------------------------------------------------------------------------------------------- #NLPin10minutes #NLPtutorial #NLPtraining #Edureka Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Instagram: https://www.instagram.com/edureka_learning/ ------------------------------------------------------------------------------------------------------- - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training, you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Natural Language Processing using Python Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learned content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics and Machine Learning have been discussed. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience. -------------------------- Who Should go for this course ? Edureka’s NLP Training is a good fit for the below professionals: From a college student having exposure to programming to a technical architect/lead in an organisation Developers aspiring to be a ‘Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Text Mining Techniques 'Python' professionals who want to design automatic predictive models on text data "This is apt for everyone” --------------------------------- Why Learn Natural Language Processing or NLP? Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users. NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data. --------------------------------- For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
Views: 57967 edureka!
Tweet Visualization and Sentiment Analysis in Python - Full Tutorial
 
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In this Python tutorial, the Tweepy module is used to stream live tweets directly from Twitter in real-time. The tweets are visualized and then the TextBlob module is used to do sentiment analysis on the tweets. 💻Code: https://github.com/vprusso/youtube_tutorials/tree/master/twitter_python ⭐️ Contents ⭐️ ⌨️ (00:06) Streaming live tweets ⌨️ (23:17) Cursor and pagination ⌨️ (43:28) Analyzing tweet data ⌨️ (1:03:16) Visualizing tweet data ⌨️ (1:20:18) Sentiment analysis 🔗Tweepy Website:http://www.tweepy.org/ 🔗Cursor Docs: http://docs.tweepy.org/en/v3.5.0/cursor_tutorial.html 🔗API Reference: http://docs.tweepy.org/en/v3.5.0/api.html Tutorial from Vincent Russo of Lucid Programming. Check out his YouTube channel: http://bit.ly/lucidcode 🐦Vincent on Twitter: @captainhamptons -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://medium.freecodecamp.org And subscribe for new videos on technology every day: https://youtube.com/subscription_center?add_user=freecodecamp
Views: 21414 freeCodeCamp.org
NLP : Python PDF Data Extraction
 
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Code : https://goo.gl/xUjhg2 Python Core ------------ Video in English https://goo.gl/df7GXL Video in Tamil https://goo.gl/LT4zEw Python Web application ---------------------- Videos in Tamil https://goo.gl/rRjs59 Videos in English https://goo.gl/spkvfv Python NLP ----------- Videos in Tamil https://goo.gl/LL4ija Videos in English https://goo.gl/TsMVfT Artificial intelligence and ML ------------------------------ Videos in Tamil https://goo.gl/VNcxUW Videos in English https://goo.gl/EiUB4P ChatBot -------- Videos in Tamil https://goo.gl/JU2WPk Videos in English https://goo.gl/KUZ7PY YouTube channel link www.youtube.com/atozknowledgevideos Website http://atozknowledge.com/ Technology in Tamil & English
Views: 13691 atoz knowledge
Python Web Scraping & Sentiment Analysis Tutorial For Beginners | Top 100  Subreddits
 
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Learn how to scrape the web and analyze sentiment using python and bs4 with TextBlob, also learn how to use the PRAW python reddit API. ► 1:1 Mentorship: https://goo.gl/P3PgC2 Code: https://github.com/jg-fisher/redditSentiment If you enjoyed this video, I would really appreciate it if you subscribed below, thanks! Also, be sure to leave any questions or feedback in the comments section.
Views: 12947 John G. Fisher
Learn Python Programming - 3 - Data Mining with Python
 
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Learn Python Programming - 3 - Data Mining with Python In this video we will learn to code a program which grabs the data which is saved in a excel file. This code will be coded with python. By Kovid Raj Panthy (Coder Kovid)
Views: 2780 Coder Kovid
Twitter Sentiment Analysis - Learn Python for Data Science #2
 
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In this video we'll be building our own Twitter Sentiment Analyzer in just 14 lines of Python. It will be able to search twitter for a list of tweets about any topic we want, then analyze each tweet to see how positive or negative it's emotion is. The coding challenge for this video is here: https://github.com/llSourcell/twitter_sentiment_challenge Naresh's winning code from last episode: https://github.com/Naresh1318/GenderClassifier/blob/master/Run_Code.py Victor's Runner up code from last episode: https://github.com/Victor-Mazzei/ml-gender-python/blob/master/gender.py I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ More on TextBlob: https://textblob.readthedocs.io/en/dev/ Great info on Sentiment Analysis: https://www.quora.com/How-does-sentiment-analysis-work Great sentiment analysis api: http://www.alchemyapi.com/products/alchemylanguage/sentiment-analysis Read over these course notes if you wanna become an NLP god: http://cs224d.stanford.edu/syllabus.html Best book to become a Python god: https://learnpythonthehardway.org/ Please share this video, like, comment and subscribe! That's what keeps me going. Feel free to support me on Patreon: https://www.patreon.com/user?u=3191693 Two Minute Papers Link: https://www.youtube.com/playlist?list=PLujxSBD-JXgnqDD1n-V30pKtp6Q886x7e Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 281227 Siraj Raval
Train a Text-Generating Neural Network for Free with textgenrnn
 
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Notebook: https://drive.google.com/file/d/1mMKGnVxirJnqDViH7BDJxFqWrsXlPSoK/view?usp=sharing Blog post: http://minimaxir.com/2018/05/text-neural-networks/ A quick guide on how you can train your own text generating neural network and generate text with it on your own computer! More about textgenrnn: https://github.com/minimaxir/textgenrnn Twitter: https://twitter.com/minimaxir Patreon: https://patreon.com/minimaxir
Views: 6839 Max Woolf
Python Tutorial - Data extraction from raw text
 
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Telegram (for Live events, Quick Questions): http://t.me/letsautomate This tutorial focuses on very basic yet powerful operations in Python, to extract meaningful information from junk data. The overall video is covers these 4 points. 1. Basic string operations for data extraction 2. How to open a text file 3. How to read rows line by line 4. Data extraction from junk Feel free to write to me with suggestions and feedback. Stay connected!
R PROGRAMMING TEXT MINING TUTORIAL
 
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Learn how to perform text analysis with R Programming through this amazing tutorial! Podcast transcript available here - https://www.superdatascience.com/sds-086-computer-vision/ Natural languages (English, Hindi, Mandarin etc.) are different from programming languages. The semantic or the meaning of a statement depends on the context, tone and a lot of other factors. Unlike programming languages, natural languages are ambiguous. Text mining deals with helping computers understand the “meaning” of the text. Some of the common text mining applications include sentiment analysis e.g if a Tweet about a movie says something positive or not, text classification e.g classifying the mails you get as spam or ham etc. In this tutorial, we’ll learn about text mining and use some R libraries to implement some common text mining techniques. We’ll learn how to do sentiment analysis, how to build word clouds, and how to process your text so that you can do meaningful analysis with it.
Views: 4113 SuperDataScience
Twitter API with Python: Part 1 -- Streaming Live Tweets
 
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In this video, we make use of the Tweepy Python module to stream live tweets directly from Twitter in real-time. In order to follow along, you will require: 1. A Twitter account, 2. Python. Assuming you have both of these, go ahead and install the "tweepy" module by running the following command inside a terminal shell. pip install tweepy Once we have this, we make a Twitter application that will be used to interface with Python code we will write, and allow us to stream and process live tweets. After creating the Twitter application, we will leverage the "tweepy" module to stream the tweets. Relevant Links: Part 1: https://www.youtube.com/watch?v=wlnx-7cm4Gg Part 2: https://www.youtube.com/watch?v=rhBZqEWsZU4 Part 3: https://www.youtube.com/watch?v=WX0MDddgpA4 Part 4: https://www.youtube.com/watch?v=w9tAoscq3C4 Part 5: https://www.youtube.com/watch?v=pdnTPUFF4gA Tweepy Website: http://www.tweepy.org/ Tweepy Docs: https://tweepy.readthedocs.io/en/v3.5.0/ Create Twitter Application: https://apps.twitter.com/ GitHub Code for this Video: https://github.com/vprusso/youtube_tutorials/tree/master/twitter_python/part_1_streaming_tweets This video is brought to you by DevMountain, a coding boot camp that offers in-person and online courses in a variety of subjects including web development, iOS development, user experience design, software quality assurance, and salesforce development. DevMountain also includes housing for full-time students. For more information: https://devmountain.com/?utm_source=Lucid%20Programming Do you like the development environment I'm using in this video? It's a customized version of vim that's enhanced for Python development. If you want to see how I set up my vim, I have a series on this here: http://bit.ly/lp_vim If you've found this video helpful and want to stay up-to-date with the latest videos posted on this channel, please subscribe: http://bit.ly/lp_subscribe
Views: 46954 LucidProgramming
TextaCy Python Tutorial - Intro and  Text Preprocessing
 
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Natural Language Processing with SpaCy and TextaCy. In this tutorial we will be learning about Textacy. Textacy is a Python library for performing higher-level natural language processing (NLP) tasks, built on the high-performance Spacy library. Textacy focuses on tasks facilitated by the availability of tokenized, POS-tagged, and parsed text ===Installation=== pip install textacy conda install -c conda-forge textacy Code: http://bit.ly/2KBf7gp Check out the Free Course on- Learn Julia Fundamentals http://bit.ly/2QLiLG8 If you liked the video don't forget to leave a like or subscribe. If you need any help just message me in the comments, you never know it might help someone else too. J-Secur1ty JCharisTech ==Get The Learn Julia App== @ Playstore : http://bit.ly/2NOiV2u @ Amazon :https://amzn.to/2OYOQdd Follow https://www.facebook.com/jcharistech/ https://github.com/Jcharis/ https://twitter.com/JCharisTech https://jcharistech.wordpress.com/
Views: 851 J-Secur1ty
Speech Recognition using Python
 
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Speech Recognition using Python Learn how to convert audio into text using python. Code here : https://github.com/umangahuja1/Youtube/blob/master/Python_Extras/speech.py Stay Tuned :) Follow here for more Quora : https://getsetpython.quora.com/ Facebook : https://www.facebook.com/getsetpython/ Twitter : https://twitter.com/umangahuja_1
Views: 143573 Get Set Python
A Quick Guide To Sentiment Analysis | Sentiment Analysis In Python Using Textblob  |  Edureka
 
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( Machine Learning Training with Python: https://www.edureka.co/python ) This video on the Sentiment Analysis in Python is a quick guide for the one who is getting started with Sentiment Analysis. Second Part: https://youtu.be/27P268Q7pE0 Check out our playlist for more videos: http://bit.ly/2taym8X Subscribe to our channel to get video updates. Hit the subscribe button above. #MachineLearningUsingPython #MachineLearningTraning #SentimentAnalysis #PythonEdureka How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience. After completing this Machine Learning Certification Training using Python, you should be able to: Gain insight into the 'Roles' played by a Machine Learning Engineer Automate data analysis using python Describe Machine Learning Work with real-time data Learn tools and techniques for predictive modeling Discuss Machine Learning algorithms and their implementation Validate Machine Learning algorithms Explain Time Series and it’s related concepts Gain expertise to handle business in future, living the present - - - - - - - - - - - - - - - - - - - Why learn Machine Learning with Python? Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning. Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 22808 edureka!
Big Data Analytics using Python and Apache Spark | Machine Learning Tutorial
 
09:28:18
Apache Spark is the most active Apache project, and it is pushing back Map Reduce. It is fast, general purpose and supports multiple programming languages, data sources and management systems. More and more organizations are adapting Apache Spark to build big data solutions through batch, interactive and stream processing paradigms. The demand for trained professionals in Spark is going through the roof. Being a new technology, there aren't enough training sources to provide easy guidance on building end-to-end solutions. Section 1: Introduction Lecture 1 About the course 08:42 Lecture 2 About V2 Maestros 01:39 Lecture 3 Resource Bundle Article Section 2: Overview Lecture 4 Hadoop Overview 10:06 Lecture 5 HDFS Architecture 14:46 Lecture 6 Map Reduce - How it works 17:24 Lecture 7 Map Reduce - Example 16:46 Lecture 8 Hadoop Stack 06:27 Lecture 9 What is Spark? 14:03 Lecture 10 Spark Architecture - Part 1 13:23 Lecture 11 Spark Architecture - Part 2 13:25 Lecture 12 Installing Spark and Setting up for Python 12:05 Quiz 1 Hadoop and Spark Architecture 5 questions Section 3: Programming with Spark Lecture 13 Spark Transformations 11:33 Lecture 14 Spark Actions 15:04 Lecture 15 Advanced Spark Programming 10:10 Lecture 16 Python - Spark Programming examples 1 16:11 Lecture 17 Python - Spark Programming Examples 2 17:18 Quiz 2 Data Engineering with Spark 5 questions Lecture 18 PRACTICE Exercise : Spark Operations Article Section 4: Spark SQL Lecture 19 Spark SQL Overview 10:03 Lecture 20 Python - Spark SQL Examples 16:16 Quiz 3 Spark SQL 2 questions Lecture 21 PRACTICE Exercise : Spark SQL Article Section 5: Spark Streaming Lecture 22 Streaming with Apache Spark 15:53 Lecture 23 Python - Spark Streaming examples 17:47 Quiz 4 Spark Streaming 3 questions Section 6: Real time Data Science Lecture 24 Basic Elements of Data Science 11:51 Lecture 25 The Dataset 10:44 Lecture 26 Learning from relationships 12:55 Lecture 27 Modeling and Prediction 09:31 Lecture 28 Data Science Use Cases 07:47 Lecture 29 Types of Analytics 12:08 Lecture 30 Types of Learning 17:16 Lecture 31 Doing Data Science in real time with Spark 07:39 Quiz 5 Spark Data Science 5 questions Section 7: Machine Learning with Spark Lecture 32 Spark Machine Learning 12:18 Lecture 33 Analyzing Results and Errors 13:46 Lecture 34 Linear Regression 19:00 Lecture 35 Spark Use Case : Linear Regression 18:33 Lecture 36 Decision Trees 10:42 Lecture 37 Spark Use Case : Decision Trees Classification 14:58 Lecture 38 Principal Component Analysis 07:28 Lecture 39 Random Forests Classification 10:31 Lecture 40 Python Use Case : Random Forests & PCA 13:16 Lecture 41 Text Preprocessing with TF-IDF 14:53 Lecture 42 Naive Bayes Classification 19:21 Lecture 43 Spark Use Case : Naive Bayes & TF-IDF 07:26 Lecture 44 K-Means Clustering 11:53 Lecture 45 Spark Use Case : K-Means 14:26 Lecture 46 Recommendation Engines 11:55 Lecture 47 Spark Use Case : Collaborative Filtering 06:34 Lecture 48 Real Time Twitter Data Sentiment Analysis 10:11 Quiz 6 Spark Machine Learning Algorithms 4 questions Lecture 49 PRACTICE Exercise : Spark Clustering Article Lecture 50 PRACTICE Exercise : Spark Classification Article Section 8: Conclusion Lecture 51 Closing Remarks 01:56 Lecture 52 BONUS Lecture : Other courses you should check out Article
Stemming And Lemmatization Tutorial | Natural Language Processing (NLP) With Python | Edureka
 
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( **Natural Language Processing Using Python: - https://www.edureka.co/python-natural-language-processing-course ** ) This video will provide you with a detailed and comprehensive knowledge of the two important aspects of Natural Language Processing ie. Stemming and Lemmatization. It will also provide you with the differences between the two with Demo on each. Following are the topics covered in this video: 0:46 - Introduction to Big Data 1:45 - What is Text Mining? 2:09- What is NLP? 3:48 - Introduction to Stemming 8:37 - Introduction to Lemmatization 10:03 - Applications of Stemming & Lemmatization 11:04 - Difference between stemming & Lemmatization Subscribe to our channel to get video updates. Hit the subscribe button above https://goo.gl/6ohpTV ----------------------------------------------------------------------------------------------- Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka ----------------------------------------------------------------------------------------------- - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Natural Language Processing using Python Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learnt content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics and Machine Learning have been discussed. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience. -------------------------- Who Should go for this course ? Edureka’s NLP Training is a good fit for the below professionals: From a college student having exposure to programming to a technical architect/lead in an organisation Developers aspiring to be a ‘Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Text Mining Techniques 'Python' professionals who want to design automatic predictive models on text data "This is apt for everyone” --------------------------------- Why Learn Natural Language Processing or NLP? Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users. NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data. --------------------------------- For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free).
Views: 4873 edureka!
Python Sentiment Analysis For Text Analytics
 
10:04
Complete project details with full project source code and database visit at : https://www.freeprojectz.com/paid-project/python-sentiment-analysis-project/text-analytics Usually, Sentimental analysis is used to determine the hidden meaning and hidden expressions present in the data format that they are positive, negative or neutral. While text analytics is generally used to analyze unstructured text data to extract associated information with it and try to convert that unstructured text data into some useful meaningful data for business intelligence. Hence, when we apply sentimental analysis for text analytics then, the hidden meaning and expression of text data are taken out in positive, negative or neutral form and later it gets properly converted into meaningful structured text data format. If you need this project then you call or whatsapp me on +91-8470010001. You can also write email us on [email protected] Premium Projects : https://www.freeprojectz.com/premium-projects Free Project Source Code and Database: https://www.freeprojectz.com/free-projects-with-source-code
Views: 329 FreeProjectz
Projects In Machine Learning | NLP for Text Classification with NLTK & Scikit-learn | Eduonix
 
01:15:40
In this tutorial, we will cover Natural Language Processing for Text Classification with NLTK & Scikit-learn. Remember the last Natural Language Processing project we did? (http://bit.ly/2Ittrop) We will be using all that information to create a Spam filter. This tutorial will also cover Feature Engineering and ensemble NLP in text classification. This project will use Jupiter Notebook running Python 2.7. Let's get started! You will find the source code to this project here: https://github.com/eduonix/nlptextclassification Check out our other Machine Learning Projects here: http://bit.ly/2HIXvvV Learn It Up! Summer’s Hottest Learning Sale Is Here! Pick Any Sun-sational Course & Get Other Absolutely FREE! Link: http://bit.ly/summer-bogo-2019 Want to learn Machine learning in detail? Then try our course Machine Learning For Absolute Beginners. Apply coupon code "YOUTUBE10" to get this course for $10 http://bit.ly/2Mi5IuP Kickstarter Campaign on AI and ML E-Degree is Launched. Back this Campaign and Explore all the Courses with over 58 Hours of Learning. Link- http://bit.ly/aimledegree Thank you for watching! We’d love to know your thoughts in the comments section below. Also, don’t forget to hit the ‘like’ button and ‘subscribe’ to ‘Eduonix Learning Solutions’ for regular updates. http://bit.ly/2ITJDQb Follow Eduonix on other social networks: ■ Facebook: https://goo.gl/ZqRVjS ■ Twitter: https://goo.gl/oRDaji ■ Google+: https://goo.gl/mfPaxx ■ Instagram: https://goo.gl/7f5DUC | @eduonix ■ Linkedin: https://goo.gl/9LLmmJ ■ Pinterest: https://goo.gl/PczPjp
Learn Python - Full Course for Beginners
 
04:26:52
This course will give you a full introduction into all of the core concepts in python. Follow along with the videos and you'll be a python programmer in no time! ⭐️ Contents ⭐ ⌨️ (0:00) Introduction ⌨️ (1:45) Installing Python & PyCharm ⌨️ (6:40) Setup & Hello World ⌨️ (10:23) Drawing a Shape ⌨️ (15:06) Variables & Data Types ⌨️ (27:03) Working With Strings ⌨️ (38:18) Working With Numbers ⌨️ (48:26) Getting Input From Users ⌨️ (52:37) Building a Basic Calculator ⌨️ (58:27) Mad Libs Game ⌨️ (1:03:10) Lists ⌨️ (1:10:44) List Functions ⌨️ (1:18:57) Tuples ⌨️ (1:24:15) Functions ⌨️ (1:34:11) Return Statement ⌨️ (1:40:06) If Statements ⌨️ (1:54:07) If Statements & Comparisons ⌨️ (2:00:37) Building a better Calculator ⌨️ (2:07:17) Dictionaries ⌨️ (2:14:13) While Loop ⌨️ (2:20:21) Building a Guessing Game ⌨️ (2:32:44) For Loops ⌨️ (2:41:20) Exponent Function ⌨️ (2:47:13) 2D Lists & Nested Loops ⌨️ (2:52:41) Building a Translator ⌨️ (3:00:18) Comments ⌨️ (3:04:17) Try / Except ⌨️ (3:12:41) Reading Files ⌨️ (3:21:26) Writing to Files ⌨️ (3:28:13) Modules & Pip ⌨️ (3:43:56) Classes & Objects ⌨️ (3:57:37) Building a Multiple Choice Quiz ⌨️ (4:08:28) Object Functions ⌨️ (4:12:37) Inheritance ⌨️ (4:20:43) Python Interpreter Course developed by Mike Dane. Check out his YouTube channel for more great programming courses: https://www.youtube.com/channel/UCvmINlrza7JHB1zkIOuXEbw 🐦Follow Mike on Twitter - https://twitter.com/mike_dane 🔗If you liked this video, Mike accepts donations on his website: https://www.mikedane.com/contribute/ ⭐️Other full courses by Mike Dane on our channel ⭐️ 💻C: https://youtu.be/KJgsSFOSQv0 💻C++: https://youtu.be/vLnPwxZdW4Y 💻SQL: https://youtu.be/HXV3zeQKqGY 💻Ruby: https://youtu.be/t_ispmWmdjY 💻PHP: https://youtu.be/OK_JCtrrv-c 💻C#: https://youtu.be/GhQdlIFylQ8 -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://medium.freecodecamp.org And subscribe for new videos on technology every day: https://youtube.com/subscription_center?add_user=freecodecamp
Views: 6304107 freeCodeCamp.org
Text Analysis and Natural Language Processing Simplified | NLP Training | Edureka
 
45:25
(NLP Certification Training: https://www.edureka.co/python-natural-language-processing-course) This video on "Text Analysis and Natural Language Processing" will provide you with in-depth knowledge of NLP, the different components of NLP and it's various applications in the industry along with a Python-based demo for each component. #nlp #deeplearning #textanalysis Subscribe to our Edureka YouTube channel to get video updates: https://goo.gl/6ohpTV --------------------------------------------------------------------------------------------- Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka ------------------------------------------------------------------------------------------------ For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
Views: 4154 edureka!
Sentiment Analysis in 4 Minutes
 
04:51
Link to the full Kaggle tutorial w/ code: https://www.kaggle.com/c/word2vec-nlp-tutorial/details/part-1-for-beginners-bag-of-words Sentiment Analysis in 5 lines of code: http://blog.dato.com/sentiment-analysis-in-five-lines-of-python I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ The Stanford Natural Language Processing course: https://class.coursera.org/nlp/lecture Cool API for sentiment analysis: http://www.alchemyapi.com/products/alchemylanguage/sentiment-analysis I recently created a Patreon page. If you like my videos, feel free to help support my effort here!: https://www.patreon.com/user?ty=h&u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 105650 Siraj Raval
Natural Language Processing (NLP) Tutorial | Data Science Tutorial | Simplilearn
 
33:22
Natural language processing (NLP) is a field of computer science, artificial intelligence and computational linguistics concerned with the interactions between computers and human (natural) languages, and, in particular, concerned with programming computers to fruitfully process large natural language corpora. Python for Data Science Certification Training Course: https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training?utm_campaign=Data-Science-NLP-6WpnxmmkYys&utm_medium=SC&utm_source=youtube The Data Science with Python course is designed to impart an in-depth knowledge of the various libraries and packages required to perform data analysis, data visualization, web scraping, machine learning, and natural language processing using Python. The course is packed with real-life projects, assignment, demos, and case studies to give a hands-on and practical experience to the participants. Mastering Python and using its packages: The course covers PROC SQL, SAS Macros, and various statistical procedures like PROC UNIVARIATE, PROC MEANS, PROC FREQ, and PROC CORP. You will learn how to use SAS for data exploration and data optimization. Mastering advanced analytics techniques: The course also covers advanced analytics techniques like clustering, decision tree, and regression. The course covers time series, it's modeling, and implementation using SAS. As a part of the course, you are provided with 4 real-life industry projects on customer segmentation, macro calls, attrition analysis, and retail analysis. Who should take this course? There is a booming demand for skilled data scientists across all industries that make this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. Analytics professionals who want to work with Python 2. Software professionals looking for a career switch in the field of analytics 3. IT professionals interested in pursuing a career in analytics 4. Graduates looking to build a career in Analytics and Data Science 5. Experienced professionals who would like to harness data science in their fields 6. Anyone with a genuine interest in the field of Data Science For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 28332 Simplilearn
Natural Language Processing in Python || Natural Language Processing Tutorial
 
01:51:04
Natural language processing (NLP) is an area of computer science and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data. Challenges in natural language processing frequently involve speech recognition, natural language understanding, and natural language generation. Natural Language Processing in Python Speaker: Alice Zhao Natural language processing (NLP) is an exciting branch of artificial intelligence (AI) that allows machines to break down and understand human language. As a data scientist, I often use NLP techniques to interpret text data that I'm working with for my analysis. During this tutorial, I plan to walk through text pre-processing techniques, machine learning techniques and Python libraries for NLP. Text pre-processing techniques include tokenization, text normalization and data cleaning. Once in a standard format, various machine learning techniques can be applied to better understand the data. This includes using popular modeling techniques to classify emails as spam or not, or to score the sentiment of a tweet on Twitter. Newer, more complex techniques can also be used such as topic modeling, word embeddings or text generation with deep learning. We will walk through an example in Jupyter Notebook that goes through all of the steps of a text analysis project, using several NLP libraries in Python including NLTK, TextBlob, spaCy and gensim along with the standard machine learning libraries including pandas and scikit-learn. ## Setup Instructions [ https://github.com/adashofdata/nlp-in-python-tutorial ) Learn From Expert = Learn Python: https://www.youtube.com/playlist?list=PLqrmzsjOpq5jHouzMfPsQ0OtZeKsIQ_h_ Machine Learning: https://www.youtube.com/playlist?list=PLqrmzsjOpq5iBQEtgHSeF4WaVzII_ycBn Data Science: https://www.youtube.com/playlist?list=PLqrmzsjOpq5gTZwO8ey_EcBMkpi4gjHob Python Pandas: https://www.youtube.com/playlist?list=PLqrmzsjOpq5jRH3uPWix4H6Ilc0NdJCPD Tech Talks From Expert: https://www.youtube.com/playlist?list=PLqrmzsjOpq5irFw0F-_XkqNXiiM1vyMoE JavaScript: https://www.youtube.com/playlist?list=PLqrmzsjOpq5hF1dIpIKZBH7AvOFyjRi8e Angular: https://www.youtube.com/playlist?list=PLqrmzsjOpq5ih8oBojNGej0oe7JsM6BGo IT Security: https://www.youtube.com/playlist?list=PLqrmzsjOpq5g5SKYrInDt0LDj0Ekflrvu IT Administration: https://www.youtube.com/playlist?list=PLqrmzsjOpq5hwvojwjsx6byUAICs_afEn Quantum Computing: https://www.youtube.com/playlist?list=PLqrmzsjOpq5iYFVnfEESpP8ErB8KcnKVC Learn SQL : https://www.youtube.com/playlist?list=PLqrmzsjOpq5jVqMfp9gUSLq9PyNBoZwdj Deep Learning: https://www.youtube.com/playlist?list=PLqrmzsjOpq5jctokAY61zrLxlE6Ub4tW_ ********************************************************** ==================================================== https://pyohio.org A FREE annual conference for anyone interested in Python in and around Ohio, the entire Midwest, maybe even the whole world. This video was published Creative Commons Attribution license (reuse allowed) Source: https://youtu.be/DqWrRpYSdio ********************************************************************
Views: 485 My CS
Scikit Learn Tutorial | Machine Learning with Python | Python for Data Science Training | Edureka
 
37:08
Python Certification Training for Data Science : https://www.edureka.co/python This Edureka video on "Scikit-learn Tutorial" introduces you to machine learning in Python. It will also takes you through regression and clustering techniques along with a demo on SVM classification on the famous iris dataset. This video helps you to learn the below topics: 1. Machine learning Overview 2. Introduction to Scikit-learn 3. Installation of Scikit-learn 4. Regression and Classification 5. Demo Subscribe to our channel to get video updates. Hit the subscribe button above. Check out our Python Training Playlist: https://goo.gl/Na1p9G #Python #PythonForDataScience #PythonTutorial #PythonForBeginners #PythonOnlineTraining How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka’s Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Python Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR. During our Python Certification Training, our instructors will help you to: 1. Master the basic and advanced concepts of Python 2. Gain insight into the 'Roles' played by a Machine Learning Engineer 3. Automate data analysis using python 4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 6. Explain Time Series and it’s related concepts 7. Perform Text Mining and Sentimental analysis 8. Gain expertise to handle business in future, living the present 9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 65002 edureka!
Intro to Data Analysis / Visualization with Python, Matplotlib and Pandas | Matplotlib Tutorial
 
22:01
Python data analysis / data science tutorial. Let’s go! For more videos like this, I’d recommend my course here: https://www.csdojo.io/moredata Sample data and sample code: https://www.csdojo.io/data My explanation about Jupyter Notebook and Anaconda: https://bit.ly/2JAtjF8 Also, keep in touch on Twitter: https://twitter.com/ykdojo And Facebook: https://www.facebook.com/entercsdojo Outline - check the comment section for a clickable version: 0:37: Why data visualization? 1:05: Why Python? 1:39: Why Matplotlib? 2:23: Installing Jupyter through Anaconda 3:20: Launching Jupyter 3:41: DEMO begins: create a folder and download data 4:27: Create a new Jupyter Notebook file 5:09: Importing libraries 6:04: Simple examples of how to use Matplotlib / Pyplot 7:21: Plotting multiple lines 8:46: Importing data from a CSV file 10:46: Plotting data you’ve imported 13:19: Using a third argument in the plot() function 13:42: A real analysis with a real data set - loading data 14:49: Isolating the data for the U.S. and China 16:29: Plotting US and China’s population growth 18:22: Comparing relative growths instead of the absolute amount 21:21: About how to get more videos like this - it’s at https://www.csdojo.io/moredata
Views: 294524 CS Dojo
Textacy Python Tutorial -  Analysis of Text (Named Entities ,NGrams)
 
08:42
Textacy Python Tutorial - Analysis of Text (Named Entities ,NGrams) In this tutorial on textacy and spacy we will be learning about how to extract named entities ,ngrams and semi structured statement with textacy in python. Code: http://bit.ly/2KBf7gp Check out the Free Course on- Learn Julia Fundamentals http://bit.ly/2QLiLG8 If you liked the video don't forget to leave a like or subscribe. If you need any help just message me in the comments, you never know it might help someone else too. J-Secur1ty JCharisTech ==Get The Learn Julia App== @ Playstore : http://bit.ly/2NOiV2u @ Amazon :https://amzn.to/2OYOQdd Follow https://www.facebook.com/jcharistech/ https://github.com/Jcharis/ https://twitter.com/JCharisTech https://jcharistech.wordpress.com/
Views: 518 J-Secur1ty
Time Series Analysis in Python | Time Series Forecasting | Data Science with Python | Edureka
 
38:20
** Python Data Science Training : https://www.edureka.co/python ** This Edureka Video on Time Series Analysis n Python will give you all the information you need to do Time Series Analysis and Forecasting in Python. Below are the topics covered in this tutorial: 1. Why Time Series? 2. What is Time Series? 3. Components of Time Series 4. When not to use Time Series 5. What is Stationarity? 6. ARIMA Model 7. Demo: Forecast Future Subscribe to our channel to get video updates. Hit the subscribe button above. Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm #timeseries #timeseriespython #machinelearningalgorithms - - - - - - - - - - - - - - - - - About the Course Edureka’s Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Python Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR. During our Python Certification Training, our instructors will help you to: 1. Master the basic and advanced concepts of Python 2. Gain insight into the 'Roles' played by a Machine Learning Engineer 3. Automate data analysis using python 4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 6. Explain Time Series and it’s related concepts 7. Perform Text Mining and Sentimental analysis 8. Gain expertise to handle business in future, living the present 9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 83117 edureka!
R vs Python | Best Programming Language for Data Science and Analysis | Edureka
 
07:19
***** Python Online Training: https://www.edureka.co/python ***** ***** R Online Training: https://www.edureka.co/r-for-analytics ***** This Edureka video on R vs Python provides you with a short and crisp description of the top two languages used in Data Science and Data Analytics i.e. Python and R (Blog:http://bit.ly/2ClaowR). You will also see the head to head comparison between the two on various parameters and learn why one is preferred over the other in certain aspects. Following topics are covered in the video: 1:30 Various Aspects of Comparison 1:40 Speed 1:56 Legacy 2:13 Code 2:28 Databases 2:45 Practical Agility 3:10 Trends 3:31 Salary 4:25 Syntax Subscribe to our Edureka YouTube channel to get video updates: https://goo.gl/6ohpTV --------------------------------------------------------------------------------------------- Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka ------------------------------------------------------------------------------------------------ #PythonVsR #Python #R #Pythononlinetraining #Javaonlinetraining ----------------------------------------------------------------- For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 90048 edureka!
Python Certification | Data Science with Python Certification | Python Online Training | Edureka
 
23:06
***** Python for Data Science Training : https://www.edureka.co/python ***** This Edureka video on "Python Certification" will give you a complete insight of Python Certification, how to crack it and hands-on knowledge on various real-time projects offered by Edureka Python Certification Training. This video will help you to learn following topics: 1. Why go for Python Certification? 2. Advantages of Python 3. Career Opportunities 4. Python Job Profiles 5. Edureka: Python Projects Subscribe to our channel to get video updates. Hit the subscribe button above. Check out our Python Training Playlist: https://goo.gl/Na1p9G #PythonCertification #PythonForDataScience #PythonForBeginners #PythonOnlineTraining How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka’s Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Python Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR. During our Python Certification Training, our instructors will help you to: 1. Master the basic and advanced concepts of Python 2. Gain insight into the 'Roles' played by a Machine Learning Engineer 3. Automate data analysis using python 4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 6. Explain Time Series and it’s related concepts 7. Perform Text Mining and Sentimental analysis 8. Gain expertise to handle business in future, living the present 9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 14231 edureka!
Coding With Python :: Learn API Basics to Grab Data with Python
 
19:23
Coding With Python :: Learn API Basics to Grab Data with Python This is a basic introduction to using APIs. APIs are the "glue" that keep a lot of web applications running and thriving. Without APIs much of the internet services you love might not even exist! APIs are easy way to connect with other websites & web services to use their data to make your site or application even better. This simple tutorial gives you the basics of how you can access this data and use it. If you want to know if a website has an api, just search "Facebook API" or "Twitter API" or "Foursquare API" on google. Some APIs are easy to use (like Locu's API which we use in this video) some are more complicated (Facebook's API is more complicated than Locu's). More about APIs: http://en.wikipedia.org/wiki/Api Code from the video: http://pastebin.com/tFeFvbXp If you want to learn more about using APIs with Django, learn at http://CodingForEntrepreneurs.com for just $25/month. We apply what we learn here into a Django web application in the GeoLocator project. The Try Django Tutorial Series is designed to help you get used to using Django in building a basic landing page (also known as splash page or MVP landing page) so you can collect data from potential users. Collecting this data will prove as verification (or validation) that your project is worth building. Furthermore, we also show you how to implement a Paypal Button so you can also accept payments. Django is awesome and very simple to get started. Step-by-step tutorials are to help you understand the workflow, get you started doing something real, then it is our goal to have you asking questions... "Why did I do X?" or "How would I do Y?" These are questions you wouldn't know to ask otherwise. Questions, after all, lead to answers. View all my videos: http://bit.ly/1a4Ienh Get Free Stuff with our Newsletter: http://eepurl.com/NmMcr The Coding For Entrepreneurs newsletter and get free deals on premium Django tutorial classes, coding for entrepreneurs courses, web hosting, marketing, and more. Oh yeah, it's free: A few ways to learn: Coding For Entrepreneurs: https://codingforentrepreneurs.com (includes free projects and free setup guides. All premium content is just $25/mo). Includes implementing Twitter Bootstrap 3, Stripe.com, django south, pip, django registration, virtual environments, deployment, basic jquery, ajax, and much more. On Udemy: Bestselling Udemy Coding for Entrepreneurs Course: https://www.udemy.com/coding-for-entrepreneurs/?couponCode=youtubecfe49 (reg $99, this link $49) MatchMaker and Geolocator Course: https://www.udemy.com/coding-for-entrepreneurs-matchmaker-geolocator/?couponCode=youtubecfe39 (advanced course, reg $75, this link: $39) Marketplace & Dail Deals Course: https://www.udemy.com/coding-for-entrepreneurs-marketplace-daily-deals/?couponCode=youtubecfe39 (advanced course, reg $75, this link: $39) Free Udemy Course (40k+ students): https://www.udemy.com/coding-for-entrepreneurs-basic/ Fun Fact! This Course was Funded on Kickstarter: http://www.kickstarter.com/projects/jmitchel3/coding-for-entrepreneurs
Views: 448946 CodingEntrepreneurs
web scraping using python for beginners
 
11:26
Learn Python here: https://courses.learncodeonline.in/learn/Python3-course In this video, we will talk about basics of web scraping using python. This is a video for total beginners, please comment if you want more videos on web scraping fb: https://www.facebook.com/HiteshChoudharyPage homepage: http://www.hiteshChoudhary.com Download LearnCodeOnline.in app from Google play store and Apple App store
Views: 191289 Hitesh Choudhary
Context Free Grammar Using NLP (Natural Language Processing) In Python | NLP Tutorial | Edureka
 
33:50
*** Natural Language Processing Course: https://www.edureka.co/python-natural-language-processing-course *** This session on Context Free Grammar will give you a detailed and comprehensive knowledge of context-free grammar and how it is used in Natual Language Processing. It also focuses on Syntax trees and Techniques like Chinking and Chunking. ------------------------------------ About this course : Edureka’s Natural Language Processing with Python course will take you through the essentials of text processing all the way up to classifying texts using Machine Learning algorithms. You will learn various concepts such as Tokenization, Stemming, Lemmatization, POS tagging, Named Entity Recognition, Syntax Tree Parsing and so on using Python’s most famous NLTK package. Once you delve into NLP, you will learn to build your own text classifier using the Naïve Bayes algorithm. ------------------------------------ Meetup: http://meetu.ps/c/4glvl/JzH2K/f Instagram: https://www.instagram.com/edureka_learning Slideshare: https://www.slideshare.net/EdurekaIN/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka For more information, please write back to us at [email protected] or call us at: IND: 9606058406 / US: 18338555775 (toll free)
Views: 2909 edureka!
K Means Clustering Algorithm | K Means Example in Python | Machine Learning Algorithms | Edureka
 
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** Python Training for Data Science: https://www.edureka.co/python ** This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) series presents another video on "K-Means Clustering Algorithm". Within the video you will learn the concepts of K-Means clustering and its implementation using python. Below are the topics covered in today's session: 1. What is Clustering? 2. Types of Clustering 3. What is K-Means Clustering? 4. How does a K-Means Algorithm works? 5. K-Means Clustering Using Python Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm Subscribe to our channel to get video updates. Hit the subscribe button above. How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Programmatically download and analyze data 2. Learn techniques to deal with different types of data – ordinal, categorical, encoding 3. Learn data visualization 4. Using I python notebooks, master the art of presenting step by step data analysis 5. Gain insight into the 'Roles' played by a Machine Learning Engineer 6. Describe Machine Learning 7. Work with real-time data 8. Learn tools and techniques for predictive modeling 9. Discuss Machine Learning algorithms and their implementation 10. Validate Machine Learning algorithms 11. Explain Time Series and its related concepts 12. Perform Text Mining and Sentimental analysis 13. Gain expertise to handle business in future, living the present - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Review Sairaam Varadarajan, Data Evangelist at Medtronic, Tempe, Arizona: "I took Big Data and Hadoop / Python course and I am planning to take Apache Mahout thus becoming the "customer of Edureka!". Instructors are knowledge... able and interactive in teaching. The sessions are well structured with a proper content in helping us to dive into Big Data / Python. Most of the online courses are free, edureka charges a minimal amount. Its acceptable for their hard-work in tailoring - All new advanced courses and its specific usage in industry. I am confident that, no other website which have tailored the courses like Edureka. It will help for an immediate take-off in Data Science and Hadoop working."
Views: 47580 edureka!
Text Mining In R | Natural Language Processing | Data Science Certification Training | Edureka
 
36:29
** Data Science Certification using R: https://www.edureka.co/data-science ** In this video on Text Mining In R, we’ll be focusing on the various methodologies used in text mining in order to retrieve useful information from data. The following topics are covered in this session: (01:18) Need for Text Mining (03:56) What Is Text Mining? (05:42) What is NLP? (07:00) Applications of NLP (08:33) Terminologies in NLP (14:09) Demo Blog Series: http://bit.ly/data-science-blogs Data Science Training Playlist: http://bit.ly/data-science-playlist - - - - - - - - - - - - - - - - - Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - - - - #textmining #textminingwithr #naturallanguageprocessing #datascience #datasciencetutorial #datasciencewithr #datasciencecourse #datascienceforbeginners #datasciencetraining #datasciencetutorial - - - - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data lifecycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modeling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyze Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyze data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies. For online Data Science training, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.
Views: 5318 edureka!
Intro to Web Scraping with Python and Beautiful Soup
 
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Web scraping is a very powerful tool to learn for any data professional. With web scraping the entire internet becomes your database. In this tutorial we show you how to parse a web page into a data file (csv) using a Python package called BeautifulSoup. In this example, we web scrape graphics cards from NewEgg.com. Sublime: https://www.sublimetext.com/3 Anaconda: https://www.anaconda.com/distribution/#download-section If you are not seeing the command line, follow this tutorial: https://www.tenforums.com/tutorials/72024-open-command-window-here-add-windows-10-a.html -- Learn more about Data Science Dojo here: https://hubs.ly/H0hz5HN0 Watch the latest video tutorials here: https://hubs.ly/H0hz5SV0 See what our past attendees are saying here: https://hubs.ly/H0hz5K20 -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 4000+ employees from over 800 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Like Us: https://www.facebook.com/datasciencedojo Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/datasciencedojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo Vimeo: https://vimeo.com/datasciencedojo #webscraping #python
Views: 537340 Data Science Dojo
Introduction - Learn Python for Data Science #1
 
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Welcome to the 1st Episode of Learn Python for Data Science! This series will teach you Python and Data Science at the same time! In this video we install Python and our text editor (Sublime Text), then build a gender classifier using the sci-kit learn library in just about 10 lines of code. Please subscribe & share this video if you liked it! The code for this video is here: https://github.com/llSourcell/gender_classification_challenge I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ Download Python here: https://www.python.org/downloads/ Download Sublime Text here: https://www.sublimetext.com/3 Some Great simple sci-kit learn examples here: https://github.com/chribsen/simple-machine-learning-examples and the official scikit website: http://scikit-learn.org/ Highly recommend this online book as supplementary reading material: https://learnpythonthehardway.org/book/ Wondering when to use which model? This chart helps, but keep in mind deep neural nets outperform pretty much any model given enough data and computing power. so use these when you don't have access to loads of data and compute: http://scikit-learn.org/stable/tutorial/machine_learning_map/ Thank you guys for watching! Subscribe, like, and comment! That's what keeps me going. Feel free to support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 516771 Siraj Raval
Python RegEx | Python Regular Expressions Tutorial |  Python Tutorial | Python Training | Edureka
 
45:34
( Python Training : https://www.edureka.co/python ) This Edureka "Python RegEx" tutorial (Python Tutorial Blog: https://goo.gl/wd28Zr) will help you in understanding how to use regular expressions in Python. You will get to learn different regular expression operations and syntaxes. You will be learning how to implement all the regex operations in python practically. Check out our playlist for more videos: https://goo.gl/Na1p9G Below are the topics covered in this tutorial: 1. Why we use Regular Expressions? 2. What are Regular Expressions? 3. Basic Regular Expressions operations 4. E-mail verification using Regular Expressions 5. Phone number verification using Regular Expressions 6. Web scraping using Regular Expressions Subscribe to our channel to get video updates. Hit the subscribe button above. #Python #PythonRegex #Pythontutorial #Pythononlinetraining #Pythonforbeginners How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Master the Basic and Advanced Concepts of Python 2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs 3. Master the Concepts of Sequences and File operations 4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python 5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 7. Master the concepts of MapReduce in Hadoop 8. Learn to write Complex MapReduce programs 9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python 10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics 11. Master the concepts of Web scraping in Python 12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. Customer Review Sairaam Varadarajan, Data Evangelist at Medtronic, Tempe, Arizona: "I took Big Data and Hadoop / Python course and I am planning to take Apache Mahout thus becoming the "customer of Edureka!". Instructors are knowledge... able and interactive in teaching. The sessions are well structured with a proper content in helping us to dive into Big Data / Python. Most of the online courses are free, edureka charges a minimal amount. Its acceptable for their hard-work in tailoring - All new advanced courses and its specific usage in industry. I am confident that, no other website which have tailored the courses like Edureka. It will help for an immediate take-off in Data Science and Hadoop working." For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 83716 edureka!
Natural Language Processing (Part 6): Text Generation with Markov Chains in Python
 
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This six-part video series goes through an end-to-end Natural Language Processing (NLP) project in Python to compare stand up comedy routines. - Natural Language Processing (Part 1): Introduction to NLP & Data Science - Natural Language Processing (Part 2): Data Cleaning & Text Pre-Processing in Python - Natural Language Processing (Part 3): Exploratory Data Analysis & Word Clouds in Python - Natural Language Processing (Part 4): Sentiment Analysis with TextBlob in Python - Natural Language Processing (Part 5): Topic Modeling with Latent Dirichlet Allocation in Python - Natural Language Processing (Part 6): Text Generation with Markov Chains in Python All of the supporting Python code can be found here: https://github.com/adashofdata/nlp-in-python-tutorial
Views: 1522 Alice Zhao
Tricks, tips and topics in Text Analysis - Bhargav Srinivasa Desikan
 
01:29:04
PyData Amsterdam 2018 There is an abundance of easily mineable text data (Whatsapp, twitter, and even our own e-mails!), and we have no excuse to not analyse it. In this workshop, we will learn some tips and tricks to deal with messy text data, before moving on to some lesser looked at text analysis techniques, such as text summarisation, working with distance metrics, and an old personal favorite - topic models. Slides: https://github.com/bhargavvader/personal/tree/master/notebooks/text_analysis_tutorial -- www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
Views: 1437 PyData
Text Summarizer App  with Tkinter and Python [NLP GUI]
 
55:22
Text Summarizer App with Tkinter and Python [Summaryzer GUI] In this tutorial we will be building a document or text summarization graphical user interface app with tkinter and spacy,sumy,gensim and nltk. Check out the Free Course on- Learn Julia Fundamentals http://bit.ly/2QLiLG8 Code For Tutorial https://github.com/Jcharis/NLP-Web-Apps/tree/master/Summaryzer_GUI If you liked the video don't forget to leave a like or subscribe. If you need any help just message me in the comments, you never know it might help someone else too. J-Secur1ty JCharisTech ==Get The Learn Julia App== @ Playstore : http://bit.ly/2NOiV2u @ Amazon :https://amzn.to/2OYOQdd Follow https://www.facebook.com/jcharistech/ https://github.com/Jcharis/ https://twitter.com/JCharisTech https://jcharistech.wordpress.com/
Views: 948 J-Secur1ty
R tutorial: The TDM & DTM with text mining
 
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Learn more about text mining with R: https://www.datacamp.com/courses/intro-to-text-mining-bag-of-words With your cleaned corpus, you need to change the data structure for analysis. The foundation of bag of words text mining is either the term document matrix or document term matrix. The term document matrix has each corpus word represented as a row with documents as columns. In this example you simply use the TermDocumentMatrix function on a corpus to create a TDM. The document term matrix is the transposition of the TDM so each document is a row and each word is a column. Once again the aptly named DocumentTermMatrix function creates a matrix with documents as rows shown here. In its simplest form, the matrices contain word frequencies. However, other frequency measures do exist. The qdap package relies on a word frequency matrix. This course doesn’t focus on the word frequency matrix, since it is less popular and can be made from a term document matrix.
Views: 16059 DataCamp
Python Tutorial: Anaconda - Installation and Using Conda
 
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In this Python Tutorial, we will be learning how to install Anaconda by Continuum Analytics. Anaconda is a data science platform that comes with a lot of useful features right out of the box. Many people find that installing Python through Anaconda is much easier than doing so manually. Also, we will look at Conda. Conda is Continuum's package, dependency and environment manager. Let's get started. Anaconda Download Page: https://www.anaconda.com/download/ ✅ Support My Channel Through Patreon: https://www.patreon.com/coreyms ✅ Become a Channel Member: https://www.youtube.com/channel/UCCezIgC97PvUuR4_gbFUs5g/join ✅ One-Time Contribution Through PayPal: https://goo.gl/649HFY ✅ Cryptocurrency Donations: Bitcoin Wallet - 3MPH8oY2EAgbLVy7RBMinwcBntggi7qeG3 Ethereum Wallet - 0x151649418616068fB46C3598083817101d3bCD33 Litecoin Wallet - MPvEBY5fxGkmPQgocfJbxP6EmTo5UUXMot ✅ Corey's Public Amazon Wishlist http://a.co/inIyro1 ✅ Equipment I Use and Books I Recommend: https://www.amazon.com/shop/coreyschafer ▶️ You Can Find Me On: My Website - http://coreyms.com/ My Second Channel - https://www.youtube.com/c/coreymschafer Facebook - https://www.facebook.com/CoreyMSchafer Twitter - https://twitter.com/CoreyMSchafer Instagram - https://www.instagram.com/coreymschafer/ #Python
Views: 613069 Corey Schafer
Keras Tutorial For Beginners | Creating Deep Learning Models Using Keras In Python | Edureka
 
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** AI & Deep Learning Training: https://www.edureka.co/ai-deep-learning-with-tensorflow ** ) This Edureka Tutorial on "Keras Tutorial" (Deep Learning Blog Series: https://goo.gl/4zxMfU) provides you a quick and insightful tutorial on the working of Keras along with an interesting use-case! We will be checking out the following topics: 00:27 Agenda 00:59 What is Keras? 01:52 Who makes Keras? 02:28 Who uses Keras? 02:54 What Makes Keras special? 05:47 Working principle of Keras 06:54 Keras Models 09:02 Understanding Execution 09:56 Implementing a Neural Network 11:36 Use-Case with Keras 15:54 Coding in Colaboratory 26:08 Session in a minute Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV Check out our Deep Learning blog series: https://bit.ly/2xVIMe1 Check out our complete Youtube playlist here: https://bit.ly/2OhZEpz ------------------------------------- Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka #Keras #KerasTutorial #DeepLearning #Python ------------------------------------- Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. About the Course Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders. Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course. - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. Business Analysts who want to understand Deep Learning (ML) Techniques 4. Information Architects who want to gain expertise in Predictive Analytics 5. Professionals who want to captivate and analyze Big Data 6. Analysts wanting to understand Data Science methodologies However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio. - - - - - - - - - - - - - - Why Learn Deep Learning With TensorFlow? TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning. Machine learning is one of the fastest-growing and most exciting fields out there, and Deep Learning represents its true bleeding edge. Deep learning is primarily a study of multi-layered neural networks, spanning over a vast range of model architectures. Traditional neural networks relied on shallow nets, composed of one input, one hidden layer and one output layer. Deep-learning networks are distinguished from these ordinary neural networks having more hidden layers, or so-called more depth. These kinds of nets are capable of discovering hidden structures within unlabeled and unstructured data (i.e. images, sound, and text), which constitutes the vast majority of data in the world. How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
Views: 21626 edureka!
How to Make a Simple Tensorflow Speech Recognizer
 
07:41
In this video, we'll make a super simple speech recognizer in 20 lines of Python using the Tensorflow machine learning library. I go over the history of speech recognition research, then explain (and rap about) how we can build our own speech recognition system using the power of deep learning. The code for this video is here: https://github.com/llSourcell/tensorflow_speech_recognition_demo Mick's winning code: https://github.com/mickvanhulst/tf_chatbot_lotr The weekly challenge can be found at the end of the 'Make a Game Bot' video: https://www.youtube.com/watch?v=mGYU5t8MO7s More learning resources: https://www.superlectures.com/iscslp2014/tutorial-4-deep-learning-for-speech-generation-and-synthesis http://andrew.gibiansky.com/blog/machine-learning/speech-recognition-neural-networks/ https://www.youtube.com/watch?v=LFDU2GX4AqM https://www.youtube.com/watch?v=g-sndkf7mCs Please subscribe! And like and comment. That's what keeps me going. And please support me on Patreon! I don't work for anyone, although I did make a one-off video for OpenAI because I love them: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 206962 Siraj Raval
Sentiment Analysis
 
10:36
Welcome to Data Lit! This 3-month course is an intro to data science for beginners. In this video, I'll explain how a popular data science technique called sentiment analysis works using a real-world scenario. We'll play the role of a data scientist working at a startup making a personal healthcare device. Using sentiment analysis, we'll understand how consumers feel about a competitors product. That'll help us make decisions on how to promote our own product, and what feature we can focus on the most. Using Python, Twitter, and Google Colab, anyone can do this process in just a few minutes. Enjoy! Code for this video: https://github.com/llSourcell/Sentiment_Analysis Please Subscribe! And Like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval instagram: https://www.instagram.com/sirajraval Facebook: https://www.facebook.com/sirajology Join us at the School of AI: https://theschool.ai/ More learning resources: https://towardsdatascience.com/sentiment-analysis-with-python-part-1-5ce197074184 https://www.geeksforgeeks.org/twitter-sentiment-analysis-using-python/ https://www.datacamp.com/community/tutorials/simplifying-sentiment-analysis-python https://www.kaggle.com/ngyptr/python-nltk-sentiment-analysis https://pythonspot.com/python-sentiment-analysis/ https://www.analyticsvidhya.com/blog/2018/07/hands-on-sentiment-analysis-dataset-python/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w #DataLit #SchoolOfAI #SirajRaval Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 52920 Siraj Raval
Complete Data Science Course | What is Data Science? | Data Science for Beginners | Edureka
 
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** Data Science Master Program: https://www.edureka.co/masters-program/data-scientist-certification ** This Edureka video on "Data Science" provides an end to end, detailed and comprehensive knowledge on Data Science. This Data Science video will start with basics of Statistics and Probability and then move to Machine Learning and Finally end the journey with Deep Learning and AI. For Data-sets and Codes discussed in this video, drop a comment. This video will be covering the following topics: 1:23 Evolution of Data 2:14 What is Data Science? 3:02 Data Science Careers 3:36 Who is a Data Analyst 4:20 Who is a Data Scientist 5:14 Who is a Machine Learning Engineer 5:44 Salary Trends 6:37 Road Map 9:06 Data Analyst Skills 10:41 Data Scientist Skills 11:47 ML Engineer Skills 12:53 Data Science Peripherals 13:17 What is Data ? 15:23 Variables & Research 17:28 Population & Sampling 20:18 Measures of Center 20:29 Measures of Spread 21:28 Skewness 21:52 Confusion Matrix 22:56 Probability 25:12 What is Machine Learning? 25:45 Features of Machine Learning 26:22 How Machine Learning works? 27:11 Applications of Machine Learning 34:57 Machine Learning Market Trends 36:05 Machine Learning Life Cycle 39:01 Important Python Libraries 40:56 Types of Machine Learning 41:07 Supervised Learning 42:27 Unsupervised Learning 43:27 Reinforcement Learning 46:27 Supervised Learning Algorithms 48:01 Linear Regression 58:12 What is Logistic Regression? 1:01:22 What is Decision Tree? 1:11:10 What is Random Forest? 1:18:48 What is Naïve Bayes? 1:30:51 Unsupervised Learning Algorithms 1:31:55 What is Clustering? 1:34:02 Types of Clustering 1:35:00 What is K-Means Clustering? 1:47:31 Market Basket Analysis 1:48:35 Association Rule Mining 1:51:22 Apriori Algorithm 2:00:46 Reinforcement Learning Algorithms 2:03:22 Reward Maximization 2:06:35 Markov Decision Process 2:08:50 Q-Learning 2:18:19 Relationship Between AI and ML and DL 2:20:10 Limitations of Machine Learning 2:21:19 What is Deep Learning ? 2:22:04 Applications of Deep Learning 2:23:35 How Neuron Works? 2:24:17 Perceptron 2:25:12 Waits and Bias 2:25:36 Activation Functions 2:29:56 Perceptron Example 2:31:48 What is TensorFlow? 2:37:05 Perceptron Problems 2:38:15 Deep Neural Network 2:39:35 Training Network Weights 2:41:04 MNIST Data set 2:41:19 Creating a Neural Network 2:50:30 Data Science Course Masters Program Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS Machine Learning Podcast: https://castbox.fm/channel/id1832236 Instagram: https://www.instagram.com/edureka_learning Slideshare: https://www.slideshare.net/EdurekaIN/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka #edureka #DataScienceEdureka #whatisdatascience #Datasciencetutorial #Datasciencecourse #datascience - - - - - - - - - - - - - - About the Master's Program This program follows a set structure with 6 core courses and 8 electives spread across 26 weeks. It makes you an expert in key technologies related to Data Science. At the end of each core course, you will be working on a real-time project to gain hands on expertise. By the end of the program you will be ready for seasoned Data Science job roles. - - - - - - - - - - - - - - Topics Covered in the curriculum: Topics covered but not limited to will be : Machine Learning, K-Means Clustering, Decision Trees, Data Mining, Python Libraries, Statistics, Scala, Spark Streaming, RDDs, MLlib, Spark SQL, Random Forest, Naïve Bayes, Time Series, Text Mining, Web Scraping, PySpark, Python Scripting, Neural Networks, Keras, TFlearn, SoftMax, Autoencoder, Restricted Boltzmann Machine, LOD Expressions, Tableau Desktop, Tableau Public, Data Visualization, Integration with R, Probability, Bayesian Inference, Regression Modelling etc. - - - - - - - - - - - - - - For more information, Please write back to us at [email protected] or call us at: IND: 9606058406 / US: 18338555775 (toll free)
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