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Use Tableau to Analyze Twitter Data - #HAPPY
 
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Tutorial on using Tableau's web data connector to connect to Twitter. I am using Tableau version 10 for this walkthrough. 1. We go to connect, select More on Server, and select Web Data Connector 2. Enter the URL of the Twitter Web Data Connector and your desired search term – If you would like to build your own Twitter web data connector you can use instructions listed on TableauJunkie’s post – http://tableaujunkie.com/post/119681578798/creating-a-twitter-web-data-connector 3. Now let’s search for the word #happy just as an example 4. Hit “Update Now” 5. We can see that we were able to get several data columns into our view – we have a. The open text – or status text b. # of times it was retweeted c. User names, locations, d. And the date that it was tweeted 6. Alright, now let’s go ahead and take a look at the data a. Let’s place user status count, and time zone country into the view and create a map view to see where @happy was tweeted b. Let’s put time zone country on label and create a filled map c. It looks like the United States is the “happiest country” according to our simple analysis d. Now let’s create a continuous area chart that will show the number of tweets as of created time – with the level of detail on minutes this is showing us how many tweets used #happy in the past few minutes e. We can turn on the labels and user time zone country add to color
Views: 5320 Story by Data
Twitter Mining Extracting Tweets In R
 
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Twitter Mining A step by step guide to extracting tweets or twitter data from twitter ! Article on How to set up Twitter Mining Yourself: https://medium.com/@randerson112358/twitter-mining-with-r-6fef0dd97781 Please Subscribe ! ►Websites: http://everythingcomputerscience.com/ ►C-Programming Tutorial: https://www.udemy.com/c-programming-for-complete-beginners/learn/v4/overview ►Become a Patreot: https://www.patreon.com/randerson112358 ►PROGRAMMING BOOKS C-Programming - https://www.amazon.com/gp/product/0131103628/ref=as_li_tl?ie=UTF8&tag=everythingc06-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=0131103628&linkId=764c7627ffb13944091b2ad15fb5de90 Head First Java - https://www.amazon.com/gp/product/0596009208/ref=as_li_tl?ie=UTF8&tag=everythingc06-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=0596009208&linkId=58082f233879197beb1aeb73b03c1ed8 ►DISCRETE STRUCTURES/MATHEMATICS BOOKS Discrete Mathematics Workbook- https://www.amazon.com/gp/product/0130463272/ref=as_li_tl?ie=UTF8&tag=everythingc06-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=0130463272&linkId=83220d3b9eb58fb0566fa51c0e5b5571 Practice Problems in Discrete Mathematics -https://www.amazon.com/gp/product/0130458031/ref=as_li_tl?ie=UTF8&tag=everythingc06-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=0130458031&linkId=e6c98555ea0342d902afda0221a1a8fb ►ALGORITHMS BOOKS Algorithm Analysis - https://www.amazon.com/gp/product/0262033844/ref=as_li_tl?ie=UTF8&tag=everythingc06-20&camp=1789&creative=9325&linkCode=as2&creativeASIN=0262033844&linkId=ba3b1d4075fbd043bb4596a0df9402e9
Views: 60 Computer Science
How to use the Twitter API v1.1 with Python to stream tweets
 
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Part 1: http://youtu.be/pUUxmvvl2FE Part 2: http://youtu.be/d-Et9uD463A Part 3: http://youtu.be/AtqqVXZ365g In this video, you are shown how to use Twitter's API v1.1 to stream tweets using Python. Twitter's on-site documentation for their API is massive, but I found it to be a bit overboard for the simple task I wanted to achieve. If you have been having trouble figuring out how to stream twitter in python, this should help you. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex Example code: http://sentdex.com/sentiment-analysisbig-data-and-python-tutorials-algorithmic-trading/how-to-use-the-twitter-api-1-1-to-stream-tweets-in-python/
Views: 151154 sentdex
Social media data mining for counter-terrorism | Wassim Zoghlami | TEDxMünster
 
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Using public social media data from twitter and Facebook, actions and announcements of terrorists – in this case ISIS – can be monitored and even be predicted. With his project #DataShield Wassim shares his idea of having a tool to identify oncoming threats and attacks in order to protect people and to induce preventive actions. Wassim Zoghlami is a Tunisian Computer Engineering Senior focussing on Business Intelligence and ERP with a passion for data science, software life cycle and UX. Wassim is also an award winning serial entrepreneur working on startups in healthcare and prevention solutions in both Tunisia and The United States. During the past years Wassim has been working on different projects and campaigns about using data driven technology to help people working to uphold human rights and to promote civic engagement and culture across Tunisia and the MENA region. He is also the co-founder of the Tunisian Center for Civic Engagement, a strong advocate for open access to research, open data and open educational resources and one of the Global Shapers in Tunis. At TEDxMünster Wassim will talk about public social media data mining for counter-terrorism and his project idea DataShield. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx
Views: 1967 TEDx Talks
Twitter Analytics with Power BI
 
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Import Twitter Data (Twitter Search) in Power BI! If you are a member of Curbal.com (it is free), you can download the file here: http://curbal.com/blog/discover-and-analyze-what-people-are-saying-in-twitter-about-your-company-with-power-bi Keynotes: Chris Koester Blog: 00:24 Create a Twitter API key 00:52 Import Twitter data into Power BI 03:18 Create a Parameters for Twitter Search 05:53 Create the first Twitter Report 08:01 Clean Twitter data with Power Query 08:20 Link to Chris' blog post: http://chris.koester.io/index.php/2015/07/16/get-data-from-twitter-api-with-power-query/ Looking for a download file? Go to our Download Center: https://curbal.com/donwload-center SUBSCRIBE to learn more about Power and Excel BI! https://www.youtube.com/channel/UCJ7UhloHSA4wAqPzyi6TOkw?sub_confirmation=1 Our PLAYLISTS: - Join our DAX Fridays! Series: https://goo.gl/FtUWUX - Power BI dashboards for beginners: https://goo.gl/9YzyDP - Power BI Tips & Tricks: https://goo.gl/H6kUbP - Power Bi and Google Analytics: https://goo.gl/ZNsY8l ABOUT CURBAL: Website: http://www.curbal.com Contact us: http://www.curbal.com/contact ▼▼▼▼▼▼▼▼▼▼ If you feel that any of the videos, downloads, blog posts that I have created have been useful to you and you want to help me keep on going, here you can do a small donation to support my work and keep the channel running: https://curbal.com/product/sponsor-me Many thanks in advance! ▲▲▲▲▲▲▲▲▲▲ QUESTIONS? COMMENTS? SUGGESTIONS? You’ll find me here: ► Twitter: @curbalen, @ruthpozuelo ► Google +: https://goo.gl/rvIBDP ► Facebook: https://goo.gl/bME2sB ► Linkedin: https://goo.gl/3VW6Ky
Views: 8737 Curbal
Sentiment Analysis in 4 Minutes
 
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Link to the full Kaggle tutorial w/ code: https://www.kaggle.com/c/word2vec-nlp-tutorial/details/part-1-for-beginners-bag-of-words Sentiment Analysis in 5 lines of code: http://blog.dato.com/sentiment-analysis-in-five-lines-of-python I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ The Stanford Natural Language Processing course: https://class.coursera.org/nlp/lecture Cool API for sentiment analysis: http://www.alchemyapi.com/products/alchemylanguage/sentiment-analysis I recently created a Patreon page. If you like my videos, feel free to help support my effort here!: https://www.patreon.com/user?ty=h&u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 94043 Siraj Raval
The Ultimate Introduction to Web Scraping and Browser Automation
 
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Whenever you need to import data from an external website, hopefully they provide an API and make your life easy. But in the real world, that's not always the case. There are numerous reasons why you might want to get data from a web page or multiple web pages, and there's no API in sight, and in that case you're going to need to fall back onto Web Scraping and Browser Automation. In this screencast I'm going to give a high level overview of how to scrape websites, then cover five different scenarios, in increasing difficulty, for practical web scraping. There is a massive amount of information in this screencast and I'm going to straight up bombard you with it, but if you can make it until the end I guarantee you will come out knowing how to scrape websites with the best of them. As always, you can hit me up on twitter @AlwaysBCoding with questions, comments, to argue about programming, or to drop a suggestion for which topics I should cover next.
Views: 151949 Decypher Media
Twitter Sentiment Analysis
 
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This tutorial shows how to conduct text sentiment analysis in R. We'll be pulling tweets from the Twitter web API, comparing each word to positive and negative word bank, and then using a basic algorithm to determine the overall sentiment. We'll then create several charts and graphs to organize the data. Updated code: http://silviaplanella.wordpress.com/2014/12/31/sentiment-analysis-twitter-and-r/ https://github.com/mjhea0/twitter-sentiment-analysis https://gist.github.com/mjhea0/5497065 TwitteR docs - http://cran.r-project.org/web/packages/twitteR/twitteR.pdf
Views: 64086 Michael Herman
Getting a list of tweets with the new Twitter REST API v1.1
 
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In this video tutorial, I'll show you how to work with the twitter API version 1.1. We'll create a php script that duplicates the functionality from the old 1.0 API so that we can pull a stream of tweets while specifying the amount, account and a callback if necessary. I'll also show you how to update a document that was calling the old API so that it works with our new document.
Views: 81093 Ray Villalobos
Twitter #2 : Classification de tweets avec Sklearn
 
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Comment classer des profils Twitter selon leurs opinions politiques (Natural Language Processing)? C'est possible avec Tweepy et Sklearn. http://www.nilsschaetti.com/ - Le code sur GitHub : https://github.com/nschaetti/NS.ai/tree/master/Tweet-Classification - L'article sur mon site web : http://www.nilsschaetti.ch/2018/01/13/opinion-mining-twitter-users-sklearn/ - Le Twitter Application Management : https://apps.twitter.com/ - La documentation de Sklearn : http://scikit-learn.org/stable/documentation.html Si vous aimez mes vidéos, soutenez-moi : - Sur Tipeee : https://www.tipeee.com/ns-ai - Sur Patreon : https://www.patreon.com/nsai Interagis avec moi : ✔ Via GitHub : https://www.github.com/nschaetti ✔ Via Twitter : https://www.twitter.com/nschaetti ✔ Via Facebook : https://www.facebook.com/NSmlai/ ✔ Via Instagram : https://www.instagram.com/n.schaetti.public
Views: 198 NS.ai
Make your own Twitter Bot with twitter4j API
 
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In this video, we discuss how to use the twitter4j API to write a program that can post tweets, retrieve tweets, and search for tweets on Twitter. In conjunction with our Chatbot Lab, one could make a functioning Twitter Bot! Our Files - http://bit.ly/MistaPotta-TwitterAPI Twitter4j jar - http://twitter4j.org/en/index.html Ria Galanos' Project - https://github.com/riagalanos/cs1-twitter
Views: 1915 mistapotta
Twitter API TweetSharp c# Твиттер АПИ создаем парсер
 
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Twitter API TweetSharp c# Твиттер АПИ создаем парсер ♔ http://socrobotic.pro/?utm_source=youtube&utm_medium=link&utm_campaign=opisanie - вся инфа о моих продуктах, акции и скидки Подпишитесь на мои ресурсы: ➡|̳̿В̳̿|контакте группа: https://vk.com/socrobotic ➡|̳̿В̳̿|контакте Личная страница: https://vk.com/denis.makarov89 ◄◄◄ ➡Канал в YouTube: https://www.youtube.com/user/makarovdenis89 Подпишитесь на мою рассылку 📥➡ https://vk.com/app5748831_-134611838 - Чтобы всегда первыми получать новые полезные материалы, рекомендации, технологии автоматизации, рызличные кейсы, бонусы и подарки!🎁 Данная рассылка производиться прямо ВКонтакте через личные сообщения, что очень удобно! ♔ Мои контакты ♔ ★ Skype: makarovdenis891 ◄◄◄ ★ Whats App: 8 (967) 67-414-96 ◄◄◄ ★ Instagram: @denis.makarov1989 ◄◄◄ Подпишись на мой канал: http://www.youtube.com/user/makarovdenis89?sub_confirmation=1
Whatsapp chat sentiment analysis in R | Sudharsan
 
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Whatsapp Chat Sentiment analysis using R programming! Subscribe to my channel for new and cool tutorials. You can also reach out to me on twitter: https://twitter.com/sudharsan1396 Code for this video: https://github.com/sudharsan13296/Whatsapp-analytics
Process Streaming Data from the Twitter using Teknek and Cassandra
 
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In this video we extract URL's from the twitter status and count them 'rainbird style' using Cassandras counters. A rather cool look at how you can quickly pipeline operators in teknek.
Views: 360 Eddie C
MAX MSP/ PROCESSING: Parsing data from Twitter, passing it with OSC
 
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Some of our most popular programs are now available over on the website: https://www.programmingforpeople.com/shop Today we are playing about with the fantastic Twitter4J library (in Processing), OSC and maxmsp. To begin with we access the twitter API using processing. Then move on to include OSC parameter passing to collect and return data to MaxMSP. A nice little project that anyone with some processing experience will be able to do! twitter4j: http://twitter4j.org Twitter tutorial processing: https://www.youtube.com/watch?v=gwS6irtGK-c on http://instagram.com/Mich_Mckellar on https://twitter.com/Mich_Mckellar email: [email protected] Look for more max help? Come and join us: https://www.facebook.com/groups/2209224391/?fref=nf
Hər gün 100 JSEcoin qazanın
 
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Views: 88 Emhm Coin
Enterprise Connectors - Social Media Data Mining
 
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This is a replay of the webinar covering using the CData Enterprise Connectors for FireDAC to connect to Twitter and Facebook to mine social media data. The examples are in Delphi, but they could also easily be adaptable for C++Builder too.
Introduction - Learn Python for Data Science #1
 
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Welcome to the 1st Episode of Learn Python for Data Science! This series will teach you Python and Data Science at the same time! In this video we install Python and our text editor (Sublime Text), then build a gender classifier using the sci-kit learn library in just about 10 lines of code. Please subscribe & share this video if you liked it! The code for this video is here: https://github.com/llSourcell/gender_classification_challenge I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ Download Python here: https://www.python.org/downloads/ Download Sublime Text here: https://www.sublimetext.com/3 Some Great simple sci-kit learn examples here: https://github.com/chribsen/simple-machine-learning-examples and the official scikit website: http://scikit-learn.org/ Highly recommend this online book as supplementary reading material: https://learnpythonthehardway.org/book/ Wondering when to use which model? This chart helps, but keep in mind deep neural nets outperform pretty much any model given enough data and computing power. so use these when you don't have access to loads of data and compute: http://scikit-learn.org/stable/tutorial/machine_learning_map/ Thank you guys for watching! Subscribe, like, and comment! That's what keeps me going. Feel free to support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 461246 Siraj Raval
Programming 7: Using Twitter API in Processing
 
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Video for introduction to real-time interactive graphical programming, using the free Processing development environment. This reflects information covered in the lab sessions for LMC 6310, Computing as an Expressive Medium, a course in the Digital Media master's program at Georgia Tech.
Views: 5598 GATechDM Courses
Facebook Comments & Twitter Tweets - Searching for Keywords
 
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Ever wanted to do some sort of data mining on tweets or facebook comments? Here's your chance with Power Pivot! use the DAX function SEARCH to look through comments for some specific keywords. Follow me on Twitter: https://twitter.com/EscobarMiguel90 Sponsor: http://www.poweredsolutions.co
Views: 2101 The Power User
Data Mining Lecture - - Finding frequent item sets | Apriori Algorithm | Solved Example (Eng-Hindi)
 
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In this video Apriori algorithm is explained in easy way in data mining Thank you for watching share with your friends Follow on : Facebook : https://www.facebook.com/wellacademy/ Instagram : https://instagram.com/well_academy Twitter : https://twitter.com/well_academy data mining in hindi, Finding frequent item sets, data mining, data mining algorithms in hindi, data mining lecture, data mining tools, data mining tutorial,
Views: 191476 Well Academy
Karthik Ramasamy: Flying faster with Twitter Heron
 
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Video from http://www.meetup.com/Data-Mining/events/224862747/
Views: 229 SF Data Mining
Extract Facebook Data and save as CSV
 
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Extract data from the Facebook Graph API using the facepager tool. Much easier for those of us who struggle with API keys ;) . Blog Post: http://davidsherlock.co.uk/using-facepager-find-comments-facebook-page-posts/
Views: 197740 David Sherlock
Data mining: opening students' personal data up to private corporations?
 
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Starting next year, the personal information of New York students will be stored in an online database created by the non-profit organization inBloom. Schools across the country are using the technology to help track students' academic progress and it's largely funded with money from the Bill and Melinda Gates Foundation. However, parents and privacy advocates across the country say that the student's data could be at risk. Kade Crockford, director of the Technology for Liberty program with the American Civil Liberties Union's Massachusetts branch, joins us to discuss if parents should be concerned or not with the emerging practice. Find RT America in your area: http://rt.com/where-to-watch/ Or watch us online: http://rt.com/on-air/rt-america-air/ Like us on Facebook http://www.facebook.com/RTAmerica Follow us on Twitter http://twitter.com/RT_America
Views: 2069 RT America
Text Mining - Using OAuth with Rapidminer
 
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Walks through how to connect to Twitter over OAuth and fetch live FIFA feeds based on a query term using Search API from Twitter with rapidminer.
Views: 2574 Sean c
Loop Operator in Rapidminer for processing Twitter Feeds
 
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Text Mining with Twitter
Views: 1768 Sean c
K-Means Clustering Algorithm - Cluster Analysis | Machine Learning Algorithm | Data Science |Edureka
 
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( Data Science Training - https://www.edureka.co/data-science ) This Edureka k-means clustering algorithm tutorial video (Data Science Blog Series: https://goo.gl/6ojfAa) will take you through the machine learning introduction, cluster analysis, types of clustering algorithms, k-means clustering, how it works along with an example/ demo in R. This Data Science with R tutorial video is ideal for beginners to learn how k-means clustering work. You can also read the blog here: https://goo.gl/QM8on4 Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #kmeans #clusteranalysis #clustering #datascience #machinelearning 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: 60872 edureka!
Decision Tree Algorithm & Analysis | Machine Learning Algorithm | Data Science Training | Edureka
 
01:21:31
( Data Science Training - https://www.edureka.co/data-science ) This Edureka Decision Tree tutorial will help you understand all the basics of Decision tree. This decision tree tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Data Science concepts, learn decision tree analysis along with examples. Below are the topics covered in this tutorial: 1) Machine Learning Introduction 2) Classification 3) Types of classifiers 4) Decision tree 5) How does Decision tree work? 6) Demo in 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 #decisiontree #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: 56609 edureka!
Detection of suicide related posts in Twitter data streams
 
12:34
2018 IEEE Transaction on Social Network For More Details::Contact::K.Manjunath - 09535866270 http://www.tmksinfotech.com and http://www.bemtechprojects.com 2018 and 2019 IEEE [email protected] TMKS Infotech,Bangalore
Views: 106 manju nath
Simple C# Console Program for Streaming Tweets Matching Your Keywords
 
09:02
Short video showing a simple C# console application that I wrote to connect to the Twitter Streaming API. This application allows you to supply a list of keywords for tracking, and using the existing TweetInvi library we receive tweet data for tweets that contain our keywords. This is meant to be a simple example, documentation for other API functions can be found on the TweetInvi github page (I am not a contributor to the TweetInvi library, this video simply uses function already written by the TweetInvi development team and I take no credit). The source code for the application in the video is available in my GitHub repository, additional video links can be found below! TweetInvi API: https://github.com/linvi/tweetinvi/wiki/Introduction (I am NOT a contributor to the TweetInvi library) Application Only API Credentials Info: https://dev.twitter.com/oauth/application-only Application Only Tokens: https://dev.twitter.com/oauth/overview/application-owner-access-tokens Twitter Apps: https://apps.twitter.com/ Video Source Code on GitHub: https://github.com/BasementProgramming/ChannelPrograms Thanks for all of the support! ~ Daniel
Views: 2198 BasementProgramming
O'Reilly Webcast: Data Science Experiments with Twitter and IPython Notebook
 
01:23:05
Want to learn the basic skills to stop talking about data science and start doing data science? After attending this mini-workshop, you'll be able to run your own data science experiments with Twitter's API and IPython Notebook! Besides learning the fundamentals of how to use IPython Notebook, you'll learn how to do the following kinds of things with Twitter's easy-to-use API: Authenticate to Twitter's API Explore the trending topics Search for tweets Filter tweets from the firehose Calculate who is following whom Compute similarity amongst Twitter users Twitter is an excellent playground for data science experiments, but the most of the concepts you'll learn generalize to other social websites like Facebook, LinkedIn, and Google+. This webcast is code-intensive, hands-on, and features lots of live examples; attendees should ideally have some minimal programming experience (or apsire to know more about the art of what's possible) to get the most out of it. About Matthew Russell Matthew Russell (@ptwobrussell) is Chief Technology Officer at Digital Reasoning, Principal at Zaffra, and author of several books on technology including Mining the Social Web (O'Reilly, 2013), now in its second edition. He is passionate about open source software development, data mining, and creating technology to amplify human intelligence. Matthew studied computer science and jumped out of airplanes at the United States Air Force Academy. When not solving hard problems, he enjoys practicing Bikram Hot Yoga, CrossFitting and participating in triathlons.
Views: 4456 O'Reilly
Jonathan Ronen - Social Networks and Protest Participation: Evidence from 130 Million Twitter Users
 
25:48
Description Data mining social networks for evidence of political participation. A demonstration of python being used to data mine the twitter conversations around the #JeSuisCharlie hashtag, and analyzing it to learn about real world protest behavior. Abstract Pinning down the role of social ties in the decision to protest has been notoriously elusive, largely due to data limitations. The era of social media and its global use by protesters offers an unprecedented opportunity to observe real-time social ties and online behavior, though often without an attendant measure of real-world behavior. We collect data on Twitter activity during the 2015 Charlie Hebdo protest in Paris which, unusually, record real-world protest attendance and high-resolution network structure. We draw on a theory of participation in which protest decisions depend on exposure to others' intentions, and network position determines exposure. Our findings are strong and consistent with this theory, showing that, relative to comparable Twitter users, protesters are significantly more connected to one another via direct, indirect, triadic, and reciprocated ties. These results offer the first large-scale empirical support for the claim that social network structure has consequences for protest participation. www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
Views: 307 PyData
data mining fp growth | data mining fp growth algorithm | data mining fp tree example | fp growth
 
14:17
In this video FP growth algorithm is explained in easy way in data mining Thank you for watching share with your friends Follow on : Facebook : https://www.facebook.com/wellacademy/ Instagram : https://instagram.com/well_academy Twitter : https://twitter.com/well_academy data mining algorithms in hindi, data mining in hindi, data mining lecture, data mining tools, data mining tutorial, data mining fp tree example, fp growth tree data mining, fp tree algorithm in data mining, fp tree algorithm in data mining example, fp tree in data mining, data mining fp growth, data mining fp growth algorithm, data mining fp tree example, data mining fp tree example, fp growth tree data mining, fp tree algorithm in data mining, fp tree algorithm in data mining example, fp tree in data mining, data mining, fp growth algorithm, fp growth algorithm example, fp growth algorithm in data mining, fp growth algorithm in data mining example, fp growth algorithm in data mining examples ppt, fp growth algorithm in data mining in hindi, fp growth algorithm in r, fp growth english, fp growth example, fp growth example in data mining, fp growth frequent itemset, fp growth in data mining, fp growth step by step, fp growth tree
Views: 123237 Well Academy
How to Download Twitter History Archive
 
03:26
This video walks you through how to request, download, and search your Twitter history archive. See more videos by Max here: https://www.youtube.com/c/MaxDalton Video Transcript: Twitter is a great platform for reaching people and getting information out there. However, searching through old tweets for something you sent out can be a nightmare, as there is no good way to see or search your archive of tweets on any of the platforms you can access Twitter through. The best way to see all of your tweets in one place where you can easily search them is to download your Twitter archive. Twitter includes an HTML interface with your archive that lets you easily search your entire history of tweets offline. Finally, it's important to note that you can only request and download your Twitter archive through the desktop version of Twitter's website, and you can't request or download your Twitter archive through the Twitter mobile app. And now, let's walk through how to request, download, and search your Twitter data archive. Step 1. Open your Web browser, navigate to twitter.com, and then log into your account. You'll land on the home screen for your Twitter account. Step 2. Click the picture associated with your profile in the upper right corner of the screen to open a drop-down menu, and then click "Settings and Privacy" in the drop-down menu. The Account screen appears. Step 3. Scroll down to locate the Content section on the right side of the screen, and then click "Request Your Archive" to the right of Your Twitter Archive toward the bottom of the content section. A dialog box appears, notifying you that your request has been received and that a link to your Twitter archive will be sent to the email address associated with your Twitter account when the information is ready. Click "Close" to close the dialog box. Step 4. Monitor the email address associated with your Twitter account. You'll eventually get an email from [email protected] with a subject line that reads It's Tweet Archive Time. Click the "Download Now" link in the email to be redirected to a Your Twitter Archive page on Twitter's website. Step 5. Click "Download" on the Your Twitter Archive page. The ZIP file containing your Twitter archive will be downloaded to your computer. Step 6. Right-click the file you downloaded to your computer, and then click "Extract All." A window appears prompting you to choose a location to extract the ZIP file contents. Choose your location, and then click "Extract." Step 7. Navigate to the extracted folder, open it, and then double-click the "Index" file to launch it in a Web browser. A simple HTML page opens. You can click an individual month block in a specific year on the right side of the screen, and all of the tweets in that month will appear on the left side of the screen. Alternatively, you can use the Search All Tweets field toward the top of the screen to search your entire tweet archive. Finally, you can click the silhouette in the upper right corner of the screen to open a drop-down menu that you can use to access your Twitter account details.
Views: 629 Max Dalton
Worked Example: Twitter API (Chapter 13)
 
19:42
http://www.py4e.com - Python for Everybody: Exploring Data in Python 3.0 Please visit the web site to access a free textbook, free supporting materials, as well as interactive exercises.
Views: 1837 Chuck Severance
Data Science Interview Questions | Data Science Tutorial | Data Science Interviews | Edureka
 
01:22:50
( Data Science Training - https://www.edureka.co/data-science ) This Data Science Interview Questions and Answers video will help you to prepare yourself for Data Science and Big Data Analytics interviews. This video is ideal for both beginners as well as professionals who want to learn or brush up their concepts in Data Science, Big Data Analytics and Machine Learning. Below are the topics covered in this tutorial: 1. Data Science Job Trends 2. Data Science Interview Questions A. Statistics Questions B. Data Analytics Questions C. Machine Learning Questions D. Probability Questions 3. Conclusion Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #DataScienceInterviewQuestions #BigDataAnalytics #DataScienceTutorial #DataScienceTraining #Datascience #Edureka 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: 73575 edureka!
How to Do Sentiment Analysis - Intro to Deep Learning #3
 
09:21
In this video, we'll use machine learning to help classify emotions! The example we'll use is classifying a movie review as either positive or negative via TF Learn in 20 lines of Python. Coding Challenge for this video: https://github.com/llSourcell/How_to_do_Sentiment_Analysis Ludo's winning code: https://github.com/ludobouan/pure-numpy-feedfowardNN See Jie Xun's runner up code: https://github.com/jiexunsee/Neural-Network-with-Python Tutorial on setting up an AMI using AWS: http://www.bitfusion.io/2016/05/09/easy-tensorflow-model-training-aws/ More learning resources: http://deeplearning.net/tutorial/lstm.html https://www.quora.com/How-is-deep-learning-used-in-sentiment-analysis https://gab41.lab41.org/deep-learning-sentiment-one-character-at-a-t-i-m-e-6cd96e4f780d#.nme2qmtll http://k8si.github.io/2016/01/28/lstm-networks-for-sentiment-analysis-on-tweets.html https://www.kaggle.com/c/word2vec-nlp-tutorial Please Subscribe! And like. And comment. That's what keeps me going. Join us in our Slack channel: wizards.herokuapp.com If you're wondering, I used style transfer via machine learning to add the fire effect to myself during the rap part. Please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 138637 Siraj Raval
Lesson 5 Basic Python for Data Analytics Social Media & Twitter Analysis
 
14:48
The objective of this channel is to give you an overview of pandas in analytics for business practitioners especially as Marketing/ Social Media Analyst tapping on big data: pandas is a DataFrame Framework, a library that stores data in a highly efficient spreadsheet format and functions. Efficient in: Data Structure (numpy) Computing time (since DataFrame is processed by C++, it runs in a well streamlined computing environment) Highly optimized and updated processes And I will end the sharing with some planned resources to help you learn analytics in the future. Feel free to access my github for Twitter Social Media Analysis (http://bit.ly/2koxDdZ) This is the playlist where I am going to explain step by step of this tutorial (https://youtu.be/YnMhFV8Q_K4) Hopefully by the end of this video you could be more inspired to learn analytics and follow through the journey Feel free to open my repository(contains powerpoint slides at): https://drive.google.com/drive/folders/0B7MOgjR94z_veUdHVGV4aENZSkk
Views: 1619 Vincent Tatan
Bigdata: Analyse de données Twitter
 
04:18
Analyse de données Twitter avec Qlik Sense Cette vidéo traite de la visualisation des informations issues de Twitter. Cela fait suite à mon article sur l'analyse de données Twitter avec Flume et Hive qui expliquait comment récupérer et analyser les tweets (http://stephane-walter.fr/?p=91)
Views: 1116 Stéphane Walter
How US Colleges & Universities Use Twitter?
 
03:26
This study employed data mining and quantitative methods to collect and analyze the available histories of primary Twitter accounts of institutions of higher education in the U.S. (n = 2411). The study comprises a sample of 5.7 million tweets, representing 62 % of all tweets created by these accounts and the entire population of U.S. colleges and universities. With this large, generalizable dataset, researchers were able to determine that the preponderance of institutional tweets are 1) monologic, 2) disseminate information (vs. eliciting action), 3) link to a relatively limited and insular ecosystem of web resources, and 4) express neutral or positive sentiment. While prior research suggests that social media can serve as a vehicle for institutions to extend their reach and further demonstrate their value to society, this article provides empirical and generalizable evidence to suggest that such innovation, in the context of institutional social media use, is limited. Download a the paper from the Innovation Higher Education here: https://link.springer.com/article/10.1007/s10755-016-9375-6 This video features the song Adventure, Darling by Gillicuddy (c) http://freemusicarchive.org/music/gillicuddy/Plays_Guitar_Again/01-adventure-darling available under a Creative Commons license.
Views: 431 Research Shorts
Mining data on Facebook with Python: 2 - Mining our Facebook posts with Python
 
05:05
After setting up our app on Facebook and after getting it to communicate with facebook-sdk we will now start to download our own posts. ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE Link to playlist: http://bit.ly/2otJDwn ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE Link to playlist: https://goo.gl/WIHiEy ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- ----- Source Code for tutorials on Youtube: http://bit.ly/2nSQSAT ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh
Views: 3104 Sukhvinder Singh
Big Data E2E Demo - Part 2/4 - Sentiment Analysis - TFIDF - Sqoop - Twitter API - Java - Python
 
31:58
NOTE: The audio speed is set to a little bit faster rate. This is part 2/4 of the E2E demo series. It focuses on: 1. Data Acquisition: A) Screen Scraping B) Twitter API C) Sqoop 2. Machine Learning: Sentiment Analysis using TF-IDF
Views: 3403 Fady El-Rukby
Using the Twitter Stream API with Max/MSP and Python
 
06:29
In this video we see how to access the real-time stream of twits filtered according to keywords. You can download the patch and the scripts from my Patreon (for free) here: https://www.patreon.com/posts/19061605 You will find the summarized steps inside the "instructions.txt" file in the download folder. You can support me on Patreon to get access to a vast amount of Max patches (mostly for the visuals using 3D graphics with Jitter) and you'll contribute to the production of my tutorials : ) Get in touch with me on my FB page: https://www.facebook.com/Federico-Foderaro-Amazing-Max-Stuff-185345661820182/
Views: 833 Amazing Max Stuff
Hacking a GPU for data ? mining show
 
46:03
Support the stream: https://streamlabs.com/brandoncoin1 Support with crypto: https://streamlabs.com/brandoncoin1#/crypto Deal of the day Asus b250 mining expert mobo https://amzn.to/2QkUA1B Crypto coin Display 10% off coupon "BrandonCoin" https://www.cryptocoindisplay.com Brandoncoin stickers https://www.etsy.com/listing/618543494/brandon-coin-v1?ref=shop_home_active_2 mining rig frame https://amzn.to/2Omx8zE Rx580 4gb https://amzn.to/2MzBoLO go follow on twitter https://twitter.com/BrandonCoin1 Ubit 4 splitter https://amzn.to/2ObbZbE z270 motherboard https://amzn.to/2LXYPxU subscriberpool.com DTube Channel https://d.tube/#!/c/brandoncoin Discord https://discord.gg/AhkKbuU BrandonCoin Website www.brandonco.in Coinbase referral link spend $100 on btc and we both get $10 free https://www.coinbase.com/join/59eff7e... YouTube Channels This Channel - https://www.youtube.com/brandoncoin Car Channel - https://www.youtube.com/motornubs Hills On Site - https://www.youtube.com/channel/UCTgP... If you would like to donate Bitcoin or Hashing power - 3GdXxx6BQe2pzH2rajtJBtP4cLr25mE8rS Brandoncoin Reddit - https://www.reddit.com/r/BrandonCoin/ Email - [email protected] Daily Mining Show 11-5-2018
Views: 825 brandon coin
Tweetinvi Tutorial - Introduction to Twitter in C#
 
07:22
This video is an introduction and tutorial to the Tweetinvi library. It gives you some answers for : * What is Tweetinvi? * How to install Tweetinvi. * How to authenticate a user on Twitter. * How to publish a Tweet. * How to retrieve the tweets from a specific user's Timeline. You can find more about tweetinvi at : https://github.com/linvi/tweetinvi If you encounter any problem with the library or the video please open an issue on https://github.com/linvi/tweetinvi/issues.
Views: 10825 Linvi
Web Scraping Donald Trump's Twitter!
 
16:00
Web Scraping Donald Trump's Twitter!
Views: 68 The Brogrammer
Cluster Twitter feeds by Device Type using Rapidminer
 
08:37
Using Rapid miner to process Twitter feeds to categorize the tweets to identify people tweeting from iPhone Twitter App, Android app or desktop etc. In a random sample of 60K tweets during FIFA semi-final match between Brazil and Germany, iPhone twitter app emerged as the winner followed by Android.
Views: 756 Sean c
Datamining Battle for Azeroth - Interview with Data Hunter Perculia of Wowhead
 
29:03
So anyone who looks up anything on the Internet related to World of Warcraft can't help but be fascinated with the datamining that Wowhead carry out on future content. I spoke to Perculia about how things look from the datamining point of view. https://www.twitter.com/thetegaming https://www.patreon.com/thete https://www.twitch.tv/thetegaming https://www.facebook.com/thetegaming/ https://www.instagram.com/thetegaming Perculia may be followed on Twitter: https://www.twitter.com/perculia Wowhead may be found at https://www.wowhead.com or Discord https://discord.gg/wowhead
Views: 2046 Thete Gaming
Twitter Analytics with Microsoft Data and BI Platform
 
15:00
Demo of doing analytics on Twitter data using the Microsoft Data Platform including Windows Azure SQL Database, HDInsight on Azure and the Microsoft BI Platform with PowerPivot, PowerView and Geoflow.
Views: 622 Dallas MTC
Facebook data mining: Obama did it first | Amanda Head
 
03:14
Amanda Head of TheRebel.media says when it comes to using Facebook to win elections, Team Obama made Trump's campaign look like amateurs... https://www.therebel.media/facebook_data_mining_obama_did_it_first_and_to_a_greater_degree_than_trump Never miss a new Rebel video: http://www.youtube.com/c/RebelMediaTV JOIN http://www.Facebook.com/JoinTheRebel *** http://www.Twitter.com/TheRebelTV
Views: 5025 Rebel Media