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The beauty of data visualization - David McCandless
 
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View full lesson: http://ed.ted.com/lessons/david-mccandless-the-beauty-of-data-visualization David McCandless turns complex data sets, like worldwide military spending, media buzz, and Facebook status updates, into beautiful, simple diagrams that tease out unseen patterns and connections. Good design, he suggests, is the best way to navigate information glut -- and it may just change the way we see the world. Talk by David McCandless.
Views: 634812 TED-Ed
Data Mining : Data Visualization Techniques
 
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This video explains various visualization techniques in data mining. Video Lecture by Anisha Lalwani.
Views: 4082 topNotch Tutorials
Data Mining and Visualization Paradata Project
 
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This is my final project for my Data mining class. Links to my information, github, and my powerpoint for research purposes: Infographic: https://infogr.am/video_games_and_viewing_them Github: https://github.com/jonlouiscool/Final-Project/tree/master Powerpoint: https://docs.google.com/presentation/d/1daRLP6r0Cw6PPKStIBwucYn2Jv8uBGnYgdWyy2YN8iI/edit?usp=sharing Sorry if the quality is low, this is due to the converter. All sources are found in the powerpoint. Hope you enjoy, and remember gaming is the future.
Views: 227 Jonlou Czajka
Introduction to Data Visualization
 
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Watch all our past and upcoming workshops on http://www.codeheroku.com In this workshop you will learn how to design custom data visualizations using JavaScript. We will use a popular JavaScript library called HighCharts to build our visualizations. What you'll learn: Choose the right tools to tell your story Fetch Data from an API Build visualizations using HighCharts Design and embed charts on your website Complete Code is here: http://www.codeheroku.com/static/workshop/code/chart.zip Sample HighCharts API used is: https://www.highcharts.com/samples/data/jsonp.php?filename=usdeur.json&callback=? Slides from the presentation are here: http://www.codeheroku.com/static/workshop/slides/Introduction-to-Data-Visualization.pdf
Views: 140 Code Heroku
Data Mining
 
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Technology students give presentation on about Data Mining including the advantages/disadvantages, how to and more.
Views: 17139 techEIU
Data Visualization Lessons
 
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This video serves as a portal to 10 other curated videos on YouTube which cover the topic of "Data Visualization" and other related topics such as "Infographics". Videos: _________________________________________ 1: The value of data visualization - http://www.youtube.com/watch?v=xekEXM0Vonc Additional Reading: - Column Five (video creator) blog: http://columnfivemedia.com/news/ - Visua.ly blog post about why data visualization is so hot: http://blog.visual.ly/why-is-data-visualization-so-hot/ - Article titled "Data visualization Past,Present, and Future": http://www.perceptualedge.com/articles/Whitepapers/Data_Visualization.pdf _________________________________________ 2: What Are Infographics? - http://www.youtube.com/watch?v=x3RTS1JfMy8 Additional Reading: - Wikipedia: http://en.wikipedia.org/wiki/Infographic - An infographic explaining what infographics are: http://www.customermagnetism.com/infographics/what-is-an-infographic/ _________________________________________ 3: Big Data Week Data Visualization London - Francesco D'Orazio "10 reasons why we visualize data" - http://www.youtube.com/watch?v=npEKPZxQuns Additional Reading: - Slides used in the video: http://www.slideshare.net/Facegroup/10-reasons-why-we-visualise-data - Blog post on why we should visualize data: http://seeingcomplexity.wordpress.com/2011/03/13/why-visualize-data-we-dont-know-yet/ - Using Data Visualization to Find Insights in Data: http://datajournalismhandbook.org/1.0/en/understanding_data_7.html _________________________________________ 4: David McCandless: The beauty of data visualization - http://www.youtube.com/watch?v=pLqjQ55tz-U Additional Reading: - David McCandless website: http://www.informationisbeautiful.net/ - The Information is Beautiful Awards website: http://www.informationisbeautifulawards.com/ - Beautiful Data blog: http://beautifuldata.net/ _________________________________________ 5: I Like Pretty Graphs: Best Practices for Data Visualization Assignments - http://www.youtube.com/watch?v=pD_OvRtH0aY Additional Reading: - Eight Principles of Data Visualization blog post: http://www.information-management.com/news/Eight-Principles-of-Data-Visualization-10023032-1.html - Design principles slides: http://www.slideshare.net/gelvan/design-principles _________________________________________ 6: How to Create Infographics Part I - http://www.youtube.com/watch?v=X4-_e8zliqg Additional Reading: - Interactive tutorial on creating an infographic: http://www.asmallbrightidea.com/pages/tutorial.html - Blog post with 5 infographics to teach you how to create infographics in powerpoint: http://blog.hubspot.com/blog/tabid/6307/bid/34223/5-Infographics-to-Teach-You-How-to-Easily-Create-Infographics-in-PowerPoint-TEMPLATES.aspx _________________________________________ 7: EFFECTIVE INFORMATION VISUALIZATION by Matthias Shapiro - EP 31 - http://www.youtube.com/watch?v=_l-Dby7-JG4 Additional Reading: - Blog post on creating effective data visualizations: http://online-behavior.com/analytics/effective-data-visualization _________________________________________ 8: Data, Design, Meaning - http://www.youtube.com/watch?v=vfYul2E56fo Additional Reading: - Idan Gazit personal website: http://gazit.me/ - Collection of Idan Gazit's slides including the ones used in the videos: https://speakerdeck.com/idangazit _________________________________________ 9: Data Viz: You're Doing it Wrong - http://www.youtube.com/watch?v=i93iWza8sG8 Additional Reading: - Common Mistakes in Data visualization slides: http://www.slideshare.net/amedeevangasse/common-mistakes-in-data-visualization - Visua.ly blog post about 4 easy visualization mistakes to avoid: http://blog.visual.ly/data-visualization-mistakes-to-avoid/ _________________________________________ 10: Designing Data Visualizations with Noah Iliinsky - http://www.youtube.com/watch?v=R-oiKt7bUU8 Additional Reading: - Noah Iliinsky books published and profile: http://www.oreillynet.com/pub/au/4419 - Noah Iliinsky virtual seminar on "Telling the Right Story With Data Visualizations": http://www.uie.com/brainsparks/2012/03/16/noah-iliinsky-telling-the-right-story/ - Noah Iliinsky podcast on "The Power of Data Visualizations": http://www.uie.com/brainsparks/2012/01/27/noah-iliinsky-the-power-of-data-visualizations/ _________________________________________
Views: 1869 JohnLio07
How to explain Data Science Using Presentation Diagrams
 
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Download: https://www.infodiagram.com/diagrams/data_science_analytics_icons_ppt_flat.html?cp=camp5 What's Data Science? How it related to Big Data? And Data Mining? Example of simple visual explanation of areas that compose Data Science - A. data sources including Big Data, B. algorithm for processing data e.g. as statistics and machine learning algorithms C. business use. Illustration of data analysis process. See inspiration how you can present these popular data related concepts visually. Using simple charts and symbols. Adapt the presentation to your context. And let me know in comments how you did it :). I'd love to hear your opinion. All this is Do It Yourself graphics using Powerpoint. Read visualization tips on IT technology slide design on my https://blog.infodiagram.com Comments are welcome!
Data Visualization 101: Visualizations To Avoid - Tableau / DataSelf
 
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About DataSelf: DataSelf Analytics is an enterprise-level analytics platform designed for every business intelligence user. It’s self-service BI at an SMB price. We start with the best technology, such as Tableau and Power BI for data discovery and visualization, DataSelf’s own data warehouse, and Microsoft BI for the back-end. Then we simplify where necessary, and we amplify by integrating everything and adding our 5000-plus out-of-the-box templates for reports, dashboards, and KPIs. DataSelf has preconfigured solutions for system such as Acumatica, Epicor, Everest Software, Infor CRM (SalesLogix), Microsoft Dynamics 365, Dynamics AX, Dynamics CRM, Dynamics GP, Dynamics NAV, Dynamics SL, NetSuite, Sage 100 (MAS 90 / MAS 200), Sage 300 (Accpac), Sage 500 (MAS 500), Sage CRM, Sage Pro, Sage X3, Salesforce, SAP Business One, Syspro, SugarCRM, xTuple, and other systems. For more information: www.dataself.com dataself.com/using-dashboard-reports-to-tell-data-story/ dataself.com/telling-story-seconds-part-2-color/ dataself.com/sage-x3-bi-analytics/ dataself.com/ms-dynamics-ax-bi-analytics/
Views: 95 DataSelf BI
Learn the essentials of data visualization
 
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How do you see your data? Just numbers in a table? Want to unlock the insights that those figures could provide if only you could present the data in a new or innovative way? In this webinar, speakers Stephanie Evergreen, a US-based expert on using research to present data effectively, and Andy Kirk, a UK-based apostle for better designed data visualization, will provide their unique takes on data viz before taking questions from webinar viewers. Evergreen runs Evergreen Data, a data presentation consulting firm with recent clients that include Time, Verizon, Adobe, World Bank, and United Nations. She is an internationally recognized data visualization expert with a PhD in research which included a dissertation on effective data presentation. Her first book, Presenting Data Effectively, was the #1 New Release in Social Sciences on Amazon in both the US and the UK for several weeks. Kirk launched his visualisingdata.com website in 2010 and became a freelance data viz consultant the next year, offering his vision to global behemoths including Disney, Intel, WHO, OECD and McKinsey. He also spent 18 months working as a co-investigator on ‘Seeing Data’ research project, funded by the Arts & Humanities Research Council and hosted by the University of Sheffield, which explored visualization literacy among the general public.
Views: 1832 SAGE
Visualizing Multivariate Data: Turning Information Into Understanding
 
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Agustin Calatroni gives a presentation on data visualization as it relates to clinical trials using real world examples from his experiences working on clinical trials related to asthma and allergy.
Views: 947 RhoInc1984
Mohammed Khan- Data Mining Final Presentation
 
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Final Presentation for Data Mining Class (Professor Zhang)
Views: 6 Mohammed Khan
Exploratory Data Analysis In Python,  Interactive Data Visualization [Course] With Python and Pandas
 
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In this Statistics Using Python Tutorial, Learn Exploratory Data Analysis In python Using data set from gapminder.org . We will code interactive graphs in Python using matplotlib and pandas within Jupyterlab. 🔷🔷🔷🔷🔷🔷🔷 Jupyter Notebooks and Data Sets for Practice: https://github.com/theengineeringworld/statistics-using-python 🔷🔷🔷🔷🔷🔷🔷 Data Cleaning Steps and Methods, How to Clean Data for Analysis With Pandas In Python [Example] 🐼 https://youtu.be/GMxCL0PBHzA Data Wrangling With Python Using Pandas, Data Science For Beginners, Statistics Using Python 🐍🐼 https://youtu.be/tqv3sL67sC8 Cleaning Data In Python Using Pandas In Data Mining Example, Statistics With Python For Data Science https://youtu.be/xcKXmXilaSw Cleaning Data In Python For Statistical Analysis Using Pandas, Big Data & Data Science For Beginners https://youtu.be/4own4ojgbnQ 🔷🔷🔷🔷🔷🔷🔷 *** Complete Python Programming Playlists *** * Python Data Science https://www.youtube.com/watch?v=Uct_EbThV1E&list=PLZ7s-Z1aAtmIbaEj_PtUqkqdmI1k7libK * NumPy Data Science Essential Training with Python 3 https://www.youtube.com/playlist?list=PLZ7s-Z1aAtmIRpnGQGMTvV3AGdDK37d2b * Python 3.6.4 Tutorial can be fund here: https://www.youtube.com/watch?v=D0FrzbmWoys&list=PLZ7s-Z1aAtmKVb0fpKyINNeSbFSNkLTjQ * Python Smart Programming in Jupyter Notebook: https://www.youtube.com/watch?v=FkJI8np1gV8&list=PLZ7s-Z1aAtmIVV0dp08_X-yDGrIlTExd2 * Python Coding Interview: https://www.youtube.com/watch?v=wwtzs7vTG50&list=PLZ7s-Z1aAtmJqtN1A3ydeMk0JoD3Lvt9g
Views: 2798 TheEngineeringWorld
Data Mining using R | Data Mining Tutorial for Beginners | R Tutorial for Beginners | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R tutorial on "Data Mining using R" will help you understand the core concepts of Data Mining comprehensively. This tutorial will also comprise of a case study using R, where you'll apply data mining operations on a real life data-set and extract information from it. Following are the topics which will be covered in the session: 1. Why Data Mining? 2. What is Data Mining 3. Knowledge Discovery in Database 4. Data Mining Tasks 5. Programming Languages for Data Mining 6. Case study using R Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #LogisticRegression #Datasciencetutorial #Datasciencecourse #datascience How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 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. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling 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. Analyse 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. Analyse 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 more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Website: https://www.edureka.co/data-science Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. " Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 77624 edureka!
Data Mining Techniques
 
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Decision Trees, Naive Bayes, and Neural Networks
Views: 23946 nathan baughman
Visual Data Representation Techniques: Combining Art and Design
 
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Representing data visually is the way to design and market your content. People are using images, videos and infographics to display information in an interactive way. How can people "see" your data and not simply read it? Here are data visualization techniques to uplift your dreary content. For more on data visualization, visit our blog: http://blog.logodesignguru.com/data-v... Want design updates? Visit our social media pages: Google: https://plus.google.com/+Logodesigngu... Twitter: https://twitter.com/LogoDesignGuru Facebook: https://www.facebook.com/LogoDesignGuru/ LinkedIn: https://www.linkedin.com/company/logodesignguru Enjoy Watching!
Views: 2191 Logo Design Guru
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Warehousing | Edureka
 
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** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ** This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial: 1. What Is The Need For BI? 2. What Is Data Warehousing? 3. Key Terminologies Related To DWH Architecture: a. OLTP Vs OLAP b. ETL c. Data Mart d. Metadata 4. DWH Architecture 5. Demo: Creating A DWH - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Intelligence playlist here: https://goo.gl/DZEuZt. #DataWarehousing #DataWarehouseTutorial #DataWarehouseTraining 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, 25 hours of assignment and 10 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 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 Data Warehousing and Business Intelligence Course, will introduce participants to create and work with leading ETL & BI tools like: 1. Talend 5.x to create, execute, monitor and schedule ETL processes. It will cover concepts around Data Replication, Migration and Integration Operations 2. Tableau 9.x for data visualization to see how easy and reliable data visualization can become for representation with dashboards 3. Data Modeling tool ERwin r9 to create a Data Warehouse or Data Mart - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Data warehousing enthusiasts 2. Analytics Managers 3. Data Modelers 4. ETL Developers and BI Developers - - - - - - - - - - - - - - Why learn Data Warehousing and Business Intelligence? All the successful companies have been investing large sums of money in business intelligence and data warehousing tools and technologies. Up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their success. With the advent of Mobile, Social and Cloud platform, today's business intelligence tools have evolved and can be categorized into five areas, including databases, extraction transformation and load (ETL) tools, data quality tools, reporting tools and statistical analysis tools. This course will provide a strong foundation around Data Warehousing and Business Intelligence fundamentals and sophisticated tools like Talend, Tableau and ERwin. - - - - - - - - - - - - - - For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - Customer Review: Kanishk says, "Underwent Mastering in DW-BI Course. The training material and trainer are up to the mark to get yourself acquainted to the new technology. Very helpful support service from Edureka."
Views: 265981 edureka!
Data Warehouse Concepts | Data Warehouse Tutorial | Data Warehouse Architecture | Edureka
 
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***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** This tutorial on data warehouse concepts will tell you everything you need to know in performing data warehousing and business intelligence. The various data warehouse concepts explained in this video are: 1. What Is Data Warehousing? 2. Data Warehousing Concepts: 3. OLAP (On-Line Analytical Processing) 4. Types Of OLAP Cubes 5. Dimensions, Facts & Measures 6. Data Warehouse Schema - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Inelligence playlist here: https://goo.gl/DZEuZt. #DataWarehousing #DataWarehouseTutorial #DataWarehouseTraining #DataWarehouseConcepts 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, 25 hours of assignment and 10 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 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 Data Warehousing and Business Intelligence Course, will introduce participants to create and work with leading ETL & BI tools like: 1. Talend 5.x to create, execute, monitor and schedule ETL processes. It will cover concepts around Data Replication, Migration and Integration Operations 2. Tableau 9.x for data visualization to see how easy and reliable data visualization can become for representation with dashboards 3. Data Modeling tool ERwin r9 to create a Data Warehouse or Data Mart - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Data warehousing enthusiasts 2. Analytics Managers 3. Data Modelers 4. ETL Developers and BI Developers - - - - - - - - - - - - - - Why learn Data Warehousing and Business Intelligence? All the successful companies have been investing large sums of money in business intelligence and data warehousing tools and technologies. Up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their success. With the advent of Mobile, Social and Cloud platform, today's business intelligence tools have evolved and can be categorized into five areas, including databases, extraction transformation and load (ETL) tools, data quality tools, reporting tools and statistical analysis tools. This course will provide a strong foundation around Data Warehousing and Business Intelligence fundamentals and sophisticated tools like Talend, Tableau and ERwin. - - - - - - - - - - - - - - For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - Customer Review: Kanishk says, "Underwent Mastering in DW-BI Course. The training material and trainer are up to the mark to get yourself acquainted to the new technology. Very helpful support service from Edureka."
Views: 57981 edureka!
Data Visualization Essentials: Visual Aspects
 
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This video is a sample from Skillsoft's video course catalog. After watching it, you will be able to design and determine the position, size, color, contrast, and shape for the data visualization. Joe Khoury is a Professional Engineer, IT Consultant, and Entrepreneur. As a professional engineer, he has logged over 8000 hours managing projects. Driven by entrepreneurial motivation, Mr. Khoury has founded and sold two IT-based businesses and has been involved in the elearning market for the better part of 12 years. Mr. Khoury writes for an IT-based elearning blog and is a published author for the IEEE. He often speaks at IT conferences on technology-based subjects globally. Skillsoft is a pioneer in the field of learning with a long history of innovation. Skillsoft provides cloud-based learning solutions for our customers worldwide, who range from global enterprises, government and education customers to mid-sized and small businesses. Learn more at http://www.skillsoft.com. https://www.linkedin.com/company/skillsoft http://www.twitter.com/skillsoft https://www.facebook.com/skillsoft
Views: 17947 Skillsoft YouTube
Tableau Tutorial for Beginners | Data Visualisation Tableau Training Introduction | Great Learning
 
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#TableauTutorial | Also watch Tableau Advanced Part 2 for Free: https://greatlearningforlife.com/tableau WHAT YOU WILL LEARN IN THIS VIDEO: When you finish this tutorial, you will be a highly proficient Tableau user, confident to apply Tableau to solve real-life problems. Access 100s of hours of similar high-quality FREE learning content at: http://greatlearningforlife.com PREREQUISITES: We assume no prior knowledge of data science, statistics or programming. This course is designed carefully to take you step by step from getting familiar with the interface, learning basic concepts to tackling more advanced topics. YOU WILL LEARN HOW TO: - Navigate the Tableau interface and perform basic operations - Import and connect to your data - Edit and save a data source - Understand Tableau terminology - Use the Tableau interface/paradigm to create powerful visualizations effectively - Create basic calculations including basic arithmetic calculations, custom aggregations and ratios, date math, and quick table calculations - Build dashboards and storyboards to share visualizations ------------------------------------------- WHY LEARN TABLEAU THROUGH THIS COURSE: - Step by Step Learning Path - Learn by Doing - Easy to follow and helps prepare for Tableau Certification - Concepts explained by solving real-life industry problems - Practical tips and tricks to save time - Taught by Industry Professionals and Tableau experts To install Tableau Public go to: http://public.tableau.com ----------------------------------------------------------------- WHY LEARN TABLEAU?: Some of you probably know exactly why you want to learn Tableau and want to get right into it. Others might still have a few questions. So, what is Tableau actually? How can it help you? How is it different from say Excel or Powerpoint? What will you actually be able to do after learning Tableau? All valid questions. A lack of data is no longer the problem. Data is everywhere. The real challenge is finding out what data is really important to your organization, being able to identify trends, causes, patterns, how to maximize your revenues or profit margins from data – so it is about being able to quickly extract actionable business insights from data. Whether you are a business intelligence analyst, a manager needing to create and analyse reports quickly or a data scientist you need to convey the great story that your data analysis is telling you. So how do you do that? Reams of numbers or pages of technical analysis won’t work – especially when your boss or higher management don’t have a background in data science or advanced statistics. What is scientifically proven is that the human brain understands large amounts of complex data best when it is presented visually – charts, graphs, plots these visual tools help to summarise and convey even the most complicated of your findings to others Sure you can do basic reports in Excel or you can make a PowerPoint presentation. But they are limited in what you can do. Or it is difficult and it will take you a lot of time and tinkering. ------------------------------------------- SO WHAT IS DIFFERENT ABOUT TABLEAU? Easy to Learn Yet Powerful – even for non-technical folks: Tableau is a software program which helps you use a drag and drop, highly visual and easy to understand interface and tools to quickly create professional level compelling visual dashboards and stories of your data. It’s easy to learn, yet is extremely powerful. ----------------------------------------- #tableau #tableauTraining #dataviz #PowerBI #BigData #Analytics #BI #infographic About Great Learning: Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U Do you know what the three pillars of Data Science? Here explaining all about thepillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: Google Plus: https://plus.google.com/u/0/108438615307549697541 Facebook: https://www.facebook.com/GreatLearningOfficial/ LinkedIn: https://www.linkedin.com/company/great-learning/
Views: 299560 Great Learning
Explore Data in Oracle Data Visualization V4
 
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In Oracle Data Visualization Desktop or Oracle Analytics Cloud..... Create a new project. Add a visualization type, add a sort, create a marquee selection, keep a selection, swap data elements, change a visualization type, save the project, and view the story. ================================= 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.
Data Visualization Design by Etan Lightstone: FutureStack 13
 
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Data visualizations have become a first class citizen of information dissemination on the web, and a powerful tool when used effectively in product user interfaces . With technologies like D3, we are able to provide a great deal of interactivity to these visualizations, and with almost unlimited possibilities. This talk will be focusing on how to design effective data visualizations: * Design process for data viz * Visual design patterns to follow * Using the right charts * Data mining, and cutting through the noise of very large data sets Be sure to subscribe and follow New Relic at: https://twitter.com/NewRelic https://www.facebook.com/NewRelic https://www.youtube.com/NewRelicInc
Views: 52936 New Relic
Data Visualization: Seeing the Story in the Data and  Learning to Effectively Communicate
 
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A presentation based, on the works of Stephen Few, presented at the Center for Literacy and Research Instruction's 50th Anniversary Conference. The presentation focuses on designing graphs that are in tune with the brain/eye perceptual subsystem, thus maximizing graph effectiveness.
Views: 9303 Tyler Rinker
The best stats you've ever seen | Hans Rosling
 
20:36
http://www.ted.com With the drama and urgency of a sportscaster, statistics guru Hans Rosling uses an amazing new presentation tool, Gapminder, to present data that debunks several myths about world development. Rosling is professor of international health at Sweden's Karolinska Institute, and founder of Gapminder, a nonprofit that brings vital global data to life. (Recorded February 2006 in Monterey, CA.) TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes. TED stands for Technology, Entertainment, Design, and TEDTalks cover these topics as well as science, business, development and the arts. Closed captions and translated subtitles in a variety of languages are now available on TED.com, at http://www.ted.com/translate. Follow us on Twitter http://www.twitter.com/tednews Checkout our Facebook page for TED exclusives https://www.facebook.com/TED
Views: 2912956 TED
Data Science In 5 Minutes | Data Science For Beginners | What Is Data Science? | Simplilearn
 
04:38
This Data Science tutorial video will give you an idea on the life of a Data Scientist, steps involved in Data science project, roles & salary offered to a Data Scientist. Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate, doubling every two years, and changing the way we live. Data Science is basically dealing with unstructured and structured data. Data Science is a field that comprises of everything that is related to data cleansing, preparation, and analysis. In simple terms, it is the umbrella of techniques used when trying to extract insights and information from data. Now, let us get started and understand what is Data Science all about. Below topics are explained in this Data Science tutorial: 1. Life of a Data Scientist 2. Steps in Data Science project - Understanding the business problem - Data acquisition - Data preparation - Exploratory data analysis - Data modeling - Visualization and communication - Deploy & maintenance 3. Roles offered to a Data Scientist 4. Salary of a Data Scientist To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Read the full article here: https://www.simplilearn.com/career-in-data-science-ultimate-guide-article?utm_campaign=What-is-Data-Science-bTTxei-S1WI&utm_medium=Tutorials&utm_source=youtube Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course. Why learn Data Science? Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data. You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to: 1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics. Install the required Python environment and other auxiliary tools and libraries 2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions 3. Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO and Weave 4. Perform data analysis and manipulation using data structures and tools provided in the Pandas package 5. Gain expertise in machine learning using the Scikit-Learn package The Data Science with python is recommended for: 1. Analytics professionals who want to work with Python 2. Software professionals looking to get into 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 Learn more at: https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training?utm_campaign=What-is-Data-Science-X3paOmcrTjQ&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn’s courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simp... - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 293288 Simplilearn
Data Mining : Visualization with Tableau
 
01:09
Home Assignment, the 1st video.
Views: 117 Ahram Kang
ggplot2 Tutorial | ggplot2 In R Tutorial | Data Visualization In R | R Training | Edureka
 
40:35
( R Training : https://www.edureka.co/r-for-analytics ) This "ggplot2 Tutorial" by Edureka is a comprehensive session on the ggplot2 in R. This tutorial will not only get you started with the ggplot2 package, but also make you an expert in visualizing data with the help of this package. This tutorial will comprise of these topics: 1) Base R Graphics 2) Grammar of Graphics 3) GGPLOT2 package Check out our R Playlist: https://goo.gl/huUh7Y Subscribe to our channel to get video updates. Hit the subscribe button above. #R #Rtutorial #Ronlinetraining #ggplot2 #ggplotinr How it Works? 1. This is a 5 Week Instructor led Online Course, 30 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 Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. During our Data Analytics with R Certification training, our instructors will help you: 1. Understand concepts around Business Intelligence and Business Analytics 2. Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others 3. Apply various supervised machine learning techniques 4. Perform Analysis of Variance (ANOVA) 5. Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc 6. Use various packages in R to create fancy plots 7. Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights - - - - - - - - - - - - - - - - - - - Who should go for this course? This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics. - - - - - - - - - - - - - - - - Why learn Data Analytics with R? The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists. Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 40226 edureka!
DAT-410: Welcome to Week Four - Visualization Design | SNHU
 
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DAT-410: Decision Support Presentation Welcome to Week Four/Module Four - Visualization Design SNHU Welcome to Week Four! There were great questions and interactions last week. I encourage you all to join in responding to your peers in the general discussion board so that we can all learn together. Keep up the good work! Last week you covered how to prepare a dataset, perform data analysis, and take research notes on your analysis. This week you will focus on how to design the visualization presentation. Data visualization is more of an art than a science. Data analysts presenting data visualizations have to learn to create visuals that represent the information being communicated. It is not an easy task, especially when starting out. However, with practice and experience, there would be an improvement in the skills needed for great data visualization. In a course on Effective Business Presentations with Powerpoint by PricewaterhouseCoopers, this eight-step approach was recommended to help in planning and delivering an effective presentation. When presenting, the impact on your audience depends on your ability to effectively deliver your message. By communicating, one learns to share ideas, initiate action, and inspire others. You will use the notes and findings from the conclusion of the data visualization step to design the data visualization presentation. There are two activities due this week. A Check-In Discussion and Milestone Two assignment. Please refer to the assignment rubric for more information. I hope you have an awesome learning experience this week! Let's begin! :) Itauma @ SNHU Southern New Hampshire University How To Create an Online Course Weekly Announcement The Art of Data Visualization
Introduction to CRISP-DM
 
00:33
Check out all of Udacity's courses at https://www.udacity.com/courses
Views: 4189 Udacity
Business Data Analysis with Excel
 
01:46:44
Lecture Starts at: 8:25 Business data presents a challenge for the data analyst. Business data is often aggregated, recorded over time, and tends to exhibit autocorrelation. Additionally, and most problematically, the amount of business data is usually quite limited. These characteristics lead to a situation where many of the tools in the analyst's tool belt (e.g., regression) aren't ideal for the task. Despite these challenges, proper analysis of business data represents a fundamental skill required of Business/Data Analysts, Product/Program Managers, and Data Scientists. At this meetup presenter Dave Langer will show how to get started analyzing business data in a robust way using Excel – no programming or statistics required! Dave will cover the following during the presentation: • The types of business data and why business data is a unique analytical challenge. • Requirements for robust business data analysis. • Using histograms, running records, and process behavior charts to analyze business data. • The rules of trend analysis. • How to properly compare business data across time, organizations, geographies, etc.Where you can learn more about the tools and techniques. *Excel spreadsheets can be found here: https://code.datasciencedojo.com/datasciencedojo/tutorials/tree/master/Business%20Data%20Analysis%20with%20Excel **Find out more about David here: https://www.meetup.com/data-science-dojo/events/236198327/ -- Learn more about Data Science Dojo here: https://hubs.ly/H0hz7sf0 Watch the latest video tutorials here: https://hubs.ly/H0hz8rL0 See what our past attendees are saying here: https://hubs.ly/H0hz7ts0 -- Like Us: https://www.facebook.com/datasciencedojo/ Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/data-science-dojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo/ Vimeo: https://vimeo.com/datasciencedojo
Views: 51316 Data Science Dojo
StatQuest: Principal Component Analysis (PCA), Step-by-Step
 
21:58
Principal Component Analysis, is one of the most useful data analysis and machine learning methods out there. It can be used to identify patterns in highly complex datasets and it can tell you what variables in your data are the most important. Lastly, it can tell you how accurate your new understanding of the data actually is. In this video, I go one step at a time through PCA, and the method used to solve it, Singular Value Decomposition. I take it nice and slowly so that the simplicity of the method is revealed and clearly explained. There is a minor error at 1:47: Points 5 and 6 are not in the right location If you are interested in doing PCA in R see: https://youtu.be/0Jp4gsfOLMs For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider a StatQuest t-shirt or sweatshirt... https://teespring.com/stores/statquest ...or buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest
Data Mining : Visualization with Tableau
 
01:00
Home Assignment, the 2nd video.
Views: 196 Ahram Kang
What Is Data Science? Data Science Course - Data Science Tutorial For Beginners | Edureka
 
01:03:05
( Data Science Training - https://www.edureka.co/data-science ) This Edureka Data Science course video (Data Science Blog Series: https://goo.gl/yGjZfs) will take you through the need of data science, what is data science, data science use cases for business, BI vs data science, data analytics tools, data science lifecycle along with a demo. This Data Science tutorial video is ideal for beginners to learn data science and machine learning basics. You can read the blog here: https://goo.gl/lYb5Lb Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #whatisdatascience #Datasciencetutorial #Datasciencecourse #datascience How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 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. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling 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. Analyse 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. Analyse 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 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 Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "
Views: 191651 edureka!
Introduction to Data Science with R - Data Analysis Part 1
 
01:21:50
Part 1 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub. NOTE - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo. Blog: http://daveondata.com GitHub: https://github.com/EasyD/IntroToDataScience I do Data Science training as a Bootcamp: https://goo.gl/OhIHSc
Views: 1017320 David Langer
Data Mining Open Flights Social Networking Presentation INFS770
 
13:47
This is a presentation created for my Final Assignment in my social networking class. It contains a social networking presentation that I analyzed in gephi.
Views: 224 Tom Austin
Webinar: Visual Tools for Big Data Network Analysis
 
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Shaunna Morrison, Carnegie Institution for Science (USA) Ahmed Eleish, Rennselear Polytechnic Institute (USA) Discover how to turn large data sets into dynamic visualizations that show network connections.
Views: 631 Deep Carbon
Brian Kent: Density Based Clustering in Python
 
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PyData NYC 2015 Clustering data into similar groups is a fundamental task in data science. Probability density-based clustering has several advantages over popular parametric methods like K-Means, but practical usage of density-based methods has lagged for computational reasons. I will discuss recent algorithmic advances that are making density-based clustering practical for larger datasets. Clustering data into similar groups is a fundamental task in data science applications such as exploratory data analysis, market segmentation, and outlier detection. Density-based clustering methods are based on the intuition that clusters are regions where many data points lie near each other, surrounded by regions without much data. Density-based methods typically have several important advantages over popular model-based methods like K-Means: they do not require users to know the number of clusters in advance, they recover clusters with more flexible shapes, and they automatically detect outliers. On the other hand, density-based clustering tends to be more computationally expensive than parametric methods, so density-based methods have not seen the same level of adoption by data scientists. Recent computational advances are changing this picture. I will talk about two density-based methods and how new Python implementations are making them more useful for larger datasets. DBSCAN is by far the most popular density-based clustering method. A new implementation in Dato's GraphLab Create machine learning package dramatically speeds up DBSCAN computation by taking advantage of GraphLab Create's multi-threaded architecture and using an algorithm based on the connected components of a similarity graph. The density Level Set Tree is a method first proposed theoretically by Chaudhuri and Dasgupta in 2010 as a way to represent a probability density function hierarchically, enabling users to use all density levels simultaneous, rather than choosing a specific level as with DBSCAN. The Python package DeBaCl implements a modification of this method and a tool for interactively visualizing the cluster hierarchy. Slides available here: https://speakerdeck.com/papayawarrior/density-based-clustering-in-python Notebooks: http://nbviewer.ipython.org/github/papayawarrior/public_talks/blob/master/pydata_nyc_dbscan.ipynb http://nbviewer.ipython.org/github/papayawarrior/public_talks/blob/master/pydata_nyc_DeBaCl.ipynb
Views: 16540 PyData
Introduction/tutorial to visual programming in Orange (python-based) a Data Mining Tool
 
34:10
Sumaiya Iqbal, Broad Institute of MIT and Hardvard & MGH is giving a overview of Orange a python-based Data Mining Tool. This tool is useful for individuals with and without programming background. Sumaiya gives examples for hierarchical clustering, PCA, prediction and text mining.
Views: 4175 Dennis Lal
Big data ppt
 
00:52
Views: 43 veera smart
Promo for "Data Visualisation with Excel" Webinar
 
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I've created a webinar called "Data Visualisation with Excel" in which you'll learn how to create charts, infographics and other data visualisations in Excel. This is a short promo for the webinar. I've created a webinar called "Create a Dashboard with Excel" in which you'll learn how to create eye-catching, informative Dashboards using Excel. This is a short promo for the webinar For more information see http://theexceltrainer.co.uk/webinar-data-visualisation-with-excel
Views: 270 Mike Thomas
Getting Started with Orange 02: Data Workflows
 
02:35
Creating a data analysis workflow in Orange data mining software. License: GNU GPL + CC Music by: http://www.bensound.com/ Website: http://orange.biolab.si/ Created by: Laboratory for Bioinformatics, Faculty of Computer and Information Science, University of Ljubljana
Views: 97009 Orange Data Mining
Visualizing Data Using t-SNE
 
55:10
Google Tech Talk June 24, 2013 (more info below) Presented by Laurens van der Maaten, Delft University of Technology, The Netherlands ABSTRACT Visualization techniques are essential tools for every data scientist. Unfortunately, the majority of visualization techniques can only be used to inspect a limited number of variables of interest simultaneously. As a result, these techniques are not suitable for big data that is very high-dimensional. An effective way to visualize high-dimensional data is to represent each data object by a two-dimensional point in such a way that similar objects are represented by nearby points, and that dissimilar objects are represented by distant points. The resulting two-dimensional points can be visualized in a scatter plot. This leads to a map of the data that reveals the underlying structure of the objects, such as the presence of clusters. We present a new technique to embed high-dimensional objects in a two-dimensional map, called t-Distributed Stochastic Neighbor Embedding (t-SNE), that produces substantially better results than alternative techniques. We demonstrate the value of t-SNE in domains such as computer vision and bioinformatics. In addition, we show how to scale up t-SNE to big data sets with millions of objects, and we present an approach to visualize objects of which the similarities are non-metric (such as semantic similarities). This talk describes joint work with Geoffrey Hinton.
Views: 126881 GoogleTechTalks
Data Visualization Techniques
 
31:41
Hear Jami Wolbers of Market Street Solutions share her insights on some basic data visualization best practices.
Views: 1407 Tennessee Analytics
Visual Analytics for Sales: Gain Insights and Answer Questions in Your Quarterly Business Review
 
03:59
For more information on visual analytics, DVCS, and a free trial, visit: https://www.oracle.com/solutions/business-analytics/data-visualization.html Making sense of your business data is critical to your organization's success. Using visual analytics to provide a deeper understanding of this data can accelerate your time to insight. For example, blending data from your reps' activities, open and closed opportunities, quota, and territory, can give you deeper insight and equip you to answer questions during your Quarterly Business Reviews (QBRs). This demo includes step-by-step instructions using Oracle Data Visualization Cloud Service (DVCS).
Views: 792 Oracle Analytics
Social Network Analysis with R | Examples
 
26:25
Social network analysis with several simple examples in R. R file: https://goo.gl/CKUuNt Data file: https://goo.gl/Ygt1rg Includes, - Social network examples - Network measures - Read data file - Create network - Histogram of node degree - Network diagram - Highlighting degrees & different layouts - Hub and authorities - Community detection R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 23307 Bharatendra Rai
Business Analytics with Excel | Data Science Tutorial | Simplilearn
 
42:30
Business Analytics with excel training has been designed to help initiate you to the world of analytics. For this we use the most commonly used analytics tool i.e. Microsoft Excel. The training will equip you with all the concepts and hard skills required to kick start your analytics career. If you already have some experience in the IT or any core industry, this course will quickly teach you how to understand data and take data driven decisions relative to your domain using Microsoft excel. Data Science Certification Training - R Programming: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training?utm_campaign=Data-Excel-W3vrMSah3rc&utm_medium=SC&utm_source=youtube For a new-comer to the analytics field, this course provides the best required foundation. The training also delves into statistical concepts which are important to derive the best insights from available data and to present the same using executive level dashboards. Finally we introduce Power BI, which is the latest and the best tool provided by Microsoft for analytics and data visualization. What are the course objectives? This course will enable you to: 1. Gain a foundational understanding of business analytics 2. Install R, R-studio, and workspace setup. You will also learn about the various R packages 3. Master the R programming and understand how various statements are executed in R 4. Gain an in-depth understanding of data structure used in R and learn to import/export data in R 5. Define, understand and use the various apply functions and DPLYP functions 6. Understand and use the various graphics in R for data visualization 7. Gain a basic understanding of the various statistical concepts 8. Understand and use hypothesis testing method to drive business decisions 9. Understand and use linear, non-linear regression models, and classification techniques for data analysis 10. Learn and use the various association rules and Apriori algorithm 11. Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: IT professionals looking for a career switch into data science and analytics Software developers looking for a career switch into data science and analytics Professionals working in data and business analytics Graduates looking to build a career in analytics and data science Anyone with a genuine interest in the data science field Experienced professionals who would like to harness data science in their fields Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields 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: 38530 Simplilearn
Slides Data mining
 
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Slides Data mining
Views: 2899 gestaodoconhecimento
Data Mining in the Retail Industry
 
07:04
This is a powerpoint/video compilation I made for a project in my Systems Engineering class. It is a tutorial of Data Mining in the Retail Industry and includes a trip I took to Harris Teeter to prove the importance of Market Basket Analysis in the real world.
Views: 7705 bgood717
In-Database Data Mining for Retail Market Basket Analysis Using Oracle Advanced Analytics
 
15:44
Market Basket Analysis presentation and demo using Oracle Advanced Analytics
Views: 10617 Charles Berger