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Videos like this “Mining Structured and Unstructured Data”
Oracle's Machine Learning & Advanced Analytics 12.2 & Oracle Data Miner 4.2 New Features
 
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Oracle's Machine Learning and Advanced Analytics 12.2 and Oracle Data Miner 4.2 New Features. This presentation highlights the new machine learning algorithms, features, functions and "differentiators" added to Oracle Database Release 12.2 and Oracle SQL Developer4.2. These features and functioned are "packaged" as part of the Oracle Advanced Analytics Database Option and Oracle Data Miner workflow UI on-premise and in the Oracle Database Cloud Service High and Extreme Editions. I hope you enjoy the video! Charlie Berger [email protected]
Views: 8914 Charlie Berger
Big Data Opportunity: Structured vs. Unstructured Data
 
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http://www.patrickschwerdtfeger.com/sbi/ Where's the opportunity in Big Data? Is it with structured data or unstructured data? Experts estimate that over 95% of the data in the world today is unstructured and only 5% is structured, so there's definitely a lot MORE unstructured data to be mined. The case histories so far suggest that the biggest opportunities lie in the messy unstructured data; the data the INCLUDES the outliers rather than marginalize them. The outliers add the most interesting insights to the process and allow the algorithms to calculate probabilities using the entire sample size, rather than relying on sampling inferences based on a small subset of the population. So research your unstructured data. Look at all those machine logs and metadata and see what insights you might be able to glean. Those are the building blocks for predictive analytics and algorithms that value.
Views: 16558 Patrick Schwerdtfeger
Tips and Tricks for Graph Data Modeling
 
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As the only NoSQL database category that prioritizes relationships, graph databases provide all the flexibility of a NoSQL database with optimized performance for connected data. Ian Robinson, Lead Engineer for Neo4j, walks you through how to model your data as a graph. He demonstrates how to avoid pitfalls early on and how to optimize your model for answering questions as Cypher queries.
Views: 18219 Neo4j
Big Data Analyics using Oracle Advanced Analytics12c and BigDataSQL
 
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Big Data Analyics using Oracle Advanced Analytics12c and Oracle Big Data SQL webcast
Views: 5345 Charlie Berger
Structured Data & Unstructured Data difference |அண்ணாச்சிக் கடையும் RDBMS உம்...#6
 
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Watsapp : +91 - 9619663272 Facebook : www.facebook.com/tamilboomiofficial Twitter : @aruforchange structured data unstructured data bigdata
Structured vs Unstructured
 
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This video covers the difference between structured and unstructured data.
Views: 40736 Robert Primmer
Extract Structured Data from unstructured Text (Text Mining Using R)
 
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A very basic example: convert unstructured data from text files to structured analyzable format.
Views: 13194 Stat Pharm
What is Oracle Analytics Cloud (OAC)?
 
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interRel presents Look Smarter Than You Are With Oracle Analytics Cloud: What is OAC? Glenn Schwartzberg
Views: 13793 interRel Consulting
Structured Data,semi structured data,unstructured data. classification of Big Data
 
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Classification of Big Data. Structured vs Unstructured data. semi-structured data. Big data & Hadoop tutorial part-2 for beginners. Hadoop tutorial. RDBMS VS Hadoop
Views: 3263 ekumeed help
Oracle Data Miner Comes of Age - Full Video.mp4
 
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This the full video of the Oracle Data Miner Comes of Age article that is in the June edition of the Oracle Scene magazine. Oracle Scene is published by the UKOUG.
Views: 4048 Brendan Tierney
Data Governance With Oracle Enterprise Data Quality
 
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A short video explaining the role of Oracle Enterprise Data Quality in your Data Governance strategy.
Views: 2789 Oracle EDQ
Вебинар "Data Mining и Text Mining: примеры решения реальных задач"
 
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Огромное количество информации представлено в неструктурированном виде, и научиться ее использовать, значит повысить эффективность работы с клиентами, увеличить продажи, быстро реагировать на жалобы, уметь оценивать результаты маркетинговых кампаний.В вебинар по Data Mining и Text Mining вам откроют дополнительные возможности для роста и расширения бизнеса. В ходе Вебинара по Data Mining и Text Mining рассмотрены возможности продуктов STATISTICA Data Miner, STATISTICA Text Miner, которые используя технологию располагают широким инструментарием для автоматического извлечения знаний из больших объемов информации. После чего в вебинаре по Data Mining и Text Mining основное внимание уделено разбору актуальных кейсов: анализу текстовой информации из веб-страниц, построению скоринговых моделей и др. Обращаем внимание, что на вебинаре по Data Mining и Text Mining дается только общий обзор методов и решений - подробная информация доступна на специализированных курсах по Data mining. http://www.statsoft.ru/products/STATISTICA_Data_Miner/ http://www.youtube.com/channel/UCmskG7TLLnSNsnwRg_lfzSA
Views: 2596 StatSoftRussia
DBMS Indexing: The Basic Concept
 
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A quick introduction to the concept of indexing in RDBMSs
Views: 172309 Brian Finnegan
Data Mining-Structured Data, Unstructured data and Information Retrieval
 
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Structured Data, Unstructured data and Information Retrieval
Views: 1367 John Paul
Oracle Data Miner 4.0/SQL Developer 4.0 Ext. - New Features
 
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Oracle Data Miner 4.0 New Features demo and presentation
Views: 10921 Charlie Berger
First Look   Advanced Analytics and Machine Learning in the Oracle Database Environment
 
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Mark Hornick and Marcos Arancibia, Oracle Advanced Analytics and Engineering Team An introduction to the machine learning capabilities and the routes data takes thru the machine learning paradigm and how to build apps that navigate the framework. ================================= To improve the video quality, click the gear icon and set the Quality to 1080p/720p HD. For more information, see http://www.oracle.com/goto/oll and http://docs.oracle.com Copyright © 2017 Oracle and/or its affiliates. Oracle is a registered trademark of Oracle and/or its affiliates. All rights reserved. Other names may be registered trademarks of their respective owners. Oracle disclaims any warranties or representations as to the accuracy or completeness of this recording, demonstration, and/or written materials (the “Materials”). The Materials are provided “as is” without any warranty of any kind, either express or implied, including without limitation warranties or merchantability, fitness for a particular purpose, and non-infringement.
Overview presentation and demonstration of Oracle Advanced Analytics Option
 
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Overview presentation & demonstration of Oracle Advanced Analytics Option.
Views: 8097 Charles Berger
Unstructured data processing with Apache Hadoop and Apache Spark
 
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This video demonstrates how easily one can use hTRUNK to extract and process Unstructured data with Apache Hadoop and Apache Spark
Views: 5196 hTRUNK
Predicting Life Time Value using Oracle Advanced Analytics
 
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Predicting Life TIme Value using Oracle Advanced Analytics, integrating with Dashboards from the Oracle Business Intelligence Enterprise Edition
Oracle data mining tutorial, data mining techniques: classification
 
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What is data mining? The Oracle Data Miner tutorial presents data mining introduction. Learn data mining techniques. More lessons, visit http://www.learn-with-video-tutorials.com/oracle-data-mining-tutorial-video
What is UNSTRUCTURED DATA? What does UNSTRUCTURED DATA mean? UNSTRUCTURED DATA meaning
 
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What is UNSTRUCTURED DATA? What does UNSTRUCTURED DATA mean? UNSTRUCTURED DATA meaning - UNSTRUCTURED DATA definition - UNSTRUCTURED DATA explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. SUBSCRIBE to our Google Earth flights channel - https://www.youtube.com/channel/UC6UuCPh7GrXznZi0Hz2YQnQ Unstructured data (or unstructured information) is information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Unstructured information is typically text-heavy, but may contain data such as dates, numbers, and facts as well. This results in irregularities and ambiguities that make it difficult to understand using traditional programs as compared to data stored in fielded form in databases or annotated (semantically tagged) in documents. In 1998, Merrill Lynch cited a rule of thumb that somewhere around 80-90% of all potentially usable business information may originate in unstructured form. This rule of thumb is not based on primary or any quantitative research, but nonetheless is accepted by some. IDC and EMC project that data will grow to 40 zettabytes by 2020, resulting in a 50-fold growth from the beginning of 2010. The Computer World magazine states that unstructured information might account for more than 70%–80% of all data in organizations. The term is imprecise for several reasons: 1. Structure, while not formally defined, can still be implied. 2. Data with some form of structure may still be characterized as unstructured if its structure is not helpful for the processing task at hand. 3. Unstructured information might have some structure (semi-structured) or even be highly structured but in ways that are unanticipated or unannounced. Techniques such as data mining, natural language processing (NLP), and text analytics provide different methods to find patterns in, or otherwise interpret, this information. Common techniques for structuring text usually involve manual tagging with metadata or part-of-speech tagging for further text mining-based structuring. The Unstructured Information Management Architecture (UIMA) standard provided a common framework for processing this information to extract meaning and create structured data about the information. Software that creates machine-processable structure can utilize the linguistic, auditory, and visual structure that exist in all forms of human communication. Algorithms can infer this inherent structure from text, for instance, by examining word morphology, sentence syntax, and other small- and large-scale patterns. Unstructured information can then be enriched and tagged to address ambiguities and relevancy-based techniques then used to facilitate search and discovery. Examples of "unstructured data" may include books, journals, documents, metadata, health records, audio, video, analog data, images, files, and unstructured text such as the body of an e-mail message, Web page, or word-processor document. While the main content being conveyed does not have a defined structure, it generally comes packaged in objects (e.g. in files or documents, …) that themselves have structure and are thus a mix of structured and unstructured data, but collectively this is still referred to as "unstructured data". For example, an HTML web page is tagged, but HTML mark-up typically serves solely for rendering. It does not capture the meaning or function of tagged elements in ways that support automated processing of the information content of the page. XHTML tagging does allow machine processing of elements, although it typically does not capture or convey the semantic meaning of tagged terms. Since unstructured data commonly occurs in electronic documents, the use of a content or document management system which can categorize entire documents is often preferred over data transfer and manipulation from within the documents. Document management thus provides the means to convey structure onto document collections. Search engines have become popular tools for indexing and searching through such data, especially text.....
Views: 1867 The Audiopedia
kmeans clustering in urdu and hindi by www.shamil.pk
 
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http://www.t4tutorials.com/kmeans-clustering-in-data-mining/ kmeans clustering in urdu and hindi by www.shamil.pk Thank you very much to https://t4tutorials.com Like Our Page: https://www.facebook.com/t4tutorialsOfficial/ For Business Queries: +923028700085 Email: [email protected]
Views: 12077 University Of Shamil
Ask the Oracle Experts Big Data Analytics with Oracle Advanced Analytics
 
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Ask the Oracle Experts continues in June with Charlie Berger Senior Director Product Management, Data Mining and Advanced Analytics. Charlie Big Data Analytics with Oracle Advanced Analytics 12 and Big Data SQL. Charlie brings analytics to life and provides real-world examples of how to use analytics.
In-Database Data Mining for Retail Market Basket Analysis Using Oracle Advanced Analytics
 
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Market Basket Analysis presentation and demo using Oracle Advanced Analytics
Views: 10574 Charles Berger
Text Mining for Beginners
 
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This is a brief introduction to text mining for beginners. Find out how text mining works and the difference between text mining and key word search, from the leader in natural language based text mining solutions. Learn more about NLP text mining in 90 seconds: https://www.youtube.com/watch?v=GdZWqYGrXww Learn more about NLP text mining for clinical risk monitoring https://www.youtube.com/watch?v=SCDaE4VRzIM
Views: 78003 Linguamatics
In-Database Data Mining Using Oracle Advanced Analytics for Classificaton using Insurance Use Case
 
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In-Database Data Mining Using Oracle Advanced Analytics Option for Classificaton using Insurance Use Case
Views: 5076 Charles Berger
Creating a Datamining model using Oracle Data Mining 11gR2
 
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Creating a Datamining model using Oracle Data Mining 11gR2 My system is: - Linux Ubuntu 10.04 (Lucid) 64 Bit - Oracle Database 11gR2 64 Bit - Oracle SQL Developer 3.0.04
Views: 6144 esinfield
Structured and Unstructured Data
 
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Data is said to be structured when it’s placed in a file with fixed fields or variables. The most familiar example of this kind of structured database is a spreadsheet, where every column is a variable and every row is a case or observation.
Views: 5823 Chee-Onn Leong
Statistics and Predictive Analytics in Oracle Database and Hadoop
 
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Statistics and Predictive Analytics in Oracle Database and Hadoop: Oracle Technology Summit - Virtual Technology Days 2015
WDM 2: Structured Data, Unstructured data and Information Retrieval
 
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What is an IR System For Full Course Experience Please Go To http://mentorsnet.org/course_preview?course_id=1 Full Course Experience Includes 1. Access to course videos and exercises 2. View & manage your progress/pace 3. In-class projects and code reviews 4. Personal guidance from your Mentors
Views: 12971 Oresoft LWC
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: 43381 edureka!
Structured vs Unstructured Data Architecture
 
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How do highly structured data systems like Oracle and unstructured Big Data systems like Hadoop interact in a big data world? Hear Andrew Waitman, Pythian's CEO discuss big data emerging trends For more information on big data visit http://www.pythian.com/services/big-data/
Views: 6288 Pythian
Machine Learning in SQL Server 2016
 
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As a competitive business, turning existing data into actionable predictions is a top priority. Microsoft SQL Server 2016 makes deploying machine learning solutions easier than ever before by enabling consumers to manipulate, transform, and make predictions on their data using custom R scripts. In this video, we show a simple restaurant recommendation engine illuminating the basics of how to write and deploy machine learning solutions in SQL Server 2016. If you have an interest in or are already writing machine learning solutions, SQL Server is a must have! Thanks for checking out our video and feel free to contact us with any questions you might have at [email protected] We love talking about this stuff!
Views: 5013 Northwest Cadence
Larry Ellison - Oracle Management Cloud and Machine Learning
 
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Larry Ellison, Executive Chairman & Chief Technology Officer, Oracle, introduces Oracle Security Monitoring and Analytics Cloud Service designed for the modern IT landscape.
Views: 1131 Oracle
How is Big Data classified?
 
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How is Big Data classified? (2018) Big Data can be classified into 3 different categories. The first one is Structured Data. The data, that does have a proper format, associated to it, can be referred to as, Structured Data. For example the data that is present within the databases, the csv files, and the excel spreadsheets can be referred to as Structured Data. The next one is Semi-Structured Data. The data, that does not have, a proper format, associated to it, can be referred to as, Semi-Structured Data. For example the data that is present within the emails, the log files and the word documents can be referred to as Semi-Structured Data. And the last one is Un-Structured Data. The data, that does not have, any format associated to it, can be referred to as, Un-Structured Data. For example the image files, the audio files and the video files can be referred to as Un-Structured Data. This is how the Big Data can be classified. Enroll into this course at a deep discounted price: https://goo.gl/HsbEC8 Please don't forget to subscribe to our channel. https://www.youtube.com/user/itskillsindemand If you like this video, please like and share it. Visit http://www.itskillsindemand.com to access the complete course. Follow Us On Facebook: https://www.facebook.com/itskillsindemand Twitter: https://twitter.com/itskillsdemand Google+: https://plus.google.com/+Itskillsindemand-com YouTube: http://www.youtube.com/user/itskillsindemand
Views: 38268 NetVersity
Sampling: Simple Random, Convenience, systematic, cluster, stratified - Statistics Help
 
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This video describes five common methods of sampling in data collection. Each has a helpful diagrammatic representation. You might like to read my blog: https://creativemaths.net/blog/
Views: 770675 Dr Nic's Maths and Stats
Loading Data into Hadoop and Using Hive
 
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Load data from a remote site into the Hadoop file system, hdfs. Using Hive, define a table definition and query the data.
Overview of Data Mining and Predictive Modelling
 
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My web page: www.imperial.ac.uk/people/n.sadawi The slides can be found here: https://github.com/nsadawi/DataMiningSlides
Views: 123977 Noureddin Sadawi
Advanced Analytics using Oracle DB EE
 
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If you’ve been wanting to expose your colleagues to the power of using the Oracle Database as a platform for predictive analytics, this special session will be perfect for you. We’ll use a combination of live demos and business use cases to explain that predictive analytics doesn’t require an advanced degree in mathematics, just a database and a few good business questions. We’ll share how to leverage the work you’ve done in building a data warehouse and collecting business data sets into solid evidence for business decisions. Predictive analytics is all about looking forward into the future and leveraging data to assess and evaluate alternative courses of action. Too often, executives and managers rely on gut instinct without using the data they already have to make better decisions. Here’s the outline for the session: - Key issues in leveraging the power of analytics - Using Oracle database as an analytics platform. - Oracle Advanced Analytics overview - Oracle Data Mining - Oracle R Enterprise - Common use cases for predictive analytics - Where to start when developing your analytics capabilities
SQL interview questions Part 1
 
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SQL Interview Questions and Answers explain Fundamentals of SQL. Usage of SQL, Advantages & Disadvantages of SQL, SQL Queries, SQL Joins, Normalization, Views, SQL Keys and Indexes. SQL stands for structural query language, is used to perform database operations like insert, delete, update and modify database.
Views: 45568 G C Reddy
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: 461741 sentdex
Parking Oracle - Machine Learning and Image Processing
 
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Machine Learning and Image Processing behind Parking Oracle.
Views: 265 Eugene Chung
What is Text Mining?
 
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An introduction to the basics of text and data mining. To learn more about text mining, view the video "How does Text Mining Work?" here: https://youtu.be/xxqrIZyKKuk
Views: 54053 Elsevier
UTL_MATCH : String Matching in Oracle
 
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Use the UTL_MATCH package to determine the similarity between two strings. For more information see: https://oracle-base.com/articles/11g/utl_match-string-matching-in-oracle Website: https://oracle-base.com Blog: https://oracle-base.com/blog Twitter: https://twitter.com/oraclebase Cameo by Danny Bryant Blog: http://dbaontap.com/ Twitter: https://twitter.com/dbcapoeira Cameo appearances are for fun, not an endorsement of the content of this video.
Views: 3369 ORACLE-BASE.com
See the Big Picture with Unstructured Data Analytics
 
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http://www.hpe.com/software/richmedia See how to extract more business value from your unstructured data. Tweet this #HPEIDOL https://www.youtube.com/results?q=%23HPEIDOL Stay up on the latest with HPE Software Big Data Follow HPE Software Big Data: @HPE_BigData https://twitter.com/HPE_BigData HPE Software LinkedIn: https://www.linkedin.com/company/hpe-software Like HPE on Facebook: https://www.facebook.com/HewlettPackardEnterprise Subscribe to HPE Technology: https://www.youtube.com/user/HewlettPackardVideos ABOUT HPE SOFTWARE IDOL Advanced enterprise search and data analytics for unstructured data with machine learning that lets you search and analyze text, image, audio, and video from virtually any source. http://www.hpe.com/software/bigdata
Views: 455 HPE Technology

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