Topics: 
Apr
2016 May News, Features
All (103) | Courses, Education (3) | Meetings (12) | News, Features (26) | Opinions, Interviews, Reports (34) | Software (5) | Tutorials, Overviews (17) | Webcasts & Webinars (6)
- Top 10 Open Dataset Resources on Github
- May 31, 2016.
The top open dataset repositories on Github include a variety of data, freely available for use by researchers, practitioners, and students alike.
- Top Stories, May 23-29: Machine Learning Key Terms, Explained; 10 Must Have Data Science Skills, Updated
- May 30, 2016.
Machine Learning Key Terms, Explained; 10 Must Have Data Science Skills, Updated; A Concise Overview of Standard Model-fitting Methods; Free eBook: Healthcare Social Media Analytics and Marketing; 7 Steps to Mastering Machine Learning With Python
- Predicting Popularity of Online Content
- May 30, 2016.
A look at predicting what makes online content popular, with a particular focus on images, especially selfies.
- Free eBook: Healthcare Social Media Analytics and Marketing
- May 27, 2016.
Get your free copy of a new ebook outlining social media marketing and analytics strategies (including code) for healthcare professionals.
- CRN Big Data Startups to Watch in 2016
- May 27, 2016.
The CRN editorial team has released its annual Big Data 100 report for 2016, which includes the 55 Big Data Startups to Watch in 2016. Get the info here.
- Data Scientist Salaries by City, Analyzed
- May 27, 2016.
This post will provide a quick overview the current state of Data Scientist salaries in the US, and performs some data analysis in concert with some additional data.
- CRN Top Data Management Technologies Vendors 2016
- May 26, 2016.
The CRN editorial team has released its annual Big Data 100 report for 2016. Check out which companies made the list of Data Management Vendors.
- Top KDnuggets tweets, May 18-24: Google supercharges #MachineLearning, #DeepLearning tasks with TPU (Tensor Processing Unit)
- May 25, 2016.
Stanford Crowd Course Initiative: #MachineLearning with #Python course; Practical Guide to Matrix Calculus for #DeepLearning; Build your own #DeepLearning Box < $1.5K
- CRN Top Platform and Tools Vendors 2016
- May 25, 2016.
The CRN editorial team has released its annual Big Data 100 report for 2016. Check out which companies made the list of Platform and Tools Vendors.
- CRN Top Business Analytics Vendors 2016
- May 24, 2016.
The CRN editorial team has released its annual Big Data 100 report for 2016. Check out which companies made the list of Business Analytics Vendors.
- Top stories, May 16-22: Annual KDnuggets Analytics Software Poll; How to Explain Machine Learning to Software Engineers
- May 23, 2016.
Annual KDnuggets Analytics Software Poll; How to Explain Machine Learning to a Software Engineer; 5 Machine Learning Projects You Can No Longer Overlook; Doing Data Science: A Kaggle Walkthrough Part 1 – Introduction
- Top KDnuggets tweets, May 11-17: Vote: What software you used for Analytics, Data Mining, Data Science projects?
- May 18, 2016.
Vote: What software you used for Analytics, Data Mining, Data Science projects? Useful #Cheatsheet: #Python, R #rstats code for #MachineLearning Algorithms; TPOT: A #Python Tool for Automating Data Science; Randomize Acceptance of Borderline Research Papers, save 25 reviewer person-years.
- Top stories for May 9-15: Data scientists mostly just do arithmetic, Data Scientists – future-proof yourselves
- May 16, 2016.
Data scientists mostly just do arithmetic and that’s a good thing; Data Scientists – future-proof yourselves; Are Deep Neural Networks Creative?; Implementing Neural Networks in Javascript; 7 Steps to Mastering Machine Learning With Python
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Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months?
- May 14, 2016.
Vote in KDnuggets 17th Annual Poll: What software you used for Analytics, Data Mining, Data Science Machine Learning projects in the past 12 months? We will clean and analyze the results and publish our analysis afterwards. - How Bing Predicts is forecasting everything from sports to political outcomes
- May 13, 2016.
Bing Predicts is an innovative feature which now regularly makes headlines for its ability to analyze massive amounts of Web activity to forecast the outcomes of elections, voting-based reality TV shows, sports matchups and more.
- Innovation in Data Analytics, help shape Singapore’s Smart Nation
- May 12, 2016.
Read a first-hand perspective on Big Data playing field in Singapore, strong support for Machine Learning and Data Science research, excellent local conditions, and how all these contribute to a bigger aspiration this city state is striving towards.
- Top KDnuggets tweets, May 4-10: Understanding the Bias-Variance Tradeoff; Python, MachineLearning, & Dueling Languages
- May 11, 2016.
Understanding the Bias-Variance Tradeoff; Python, MachineLearning, & Dueling Languages; Why AI development is going to get even faster; Why Implement #MachineLearning Algorithms From Scratch?
- Top Talks and Tutorials From PyData London
- May 11, 2016.
Get some insight into the most recent Python data science talks and presentations with this eclectic mix of videos from PyData London 2016.
- Top stories for May 1-7: Why Implement Machine Learning Algorithms From Scratch? 7 Steps to Mastering Machine Learning With Python
- May 8, 2016.
How to Use Cohort Analysis to Improve Customer Retention; Why Implement Machine Learning Algorithms From Scratch?; 7 Steps to Mastering Machine Learning With Python; R vs Python for Data Science: The Winner is ...
- Meet the 11 Big Data & Data Science Leaders on LinkedIn
- May 6, 2016.
In this post, we present a list of popular data science leaders on LinkedIn. Follow these leaders who will keep you in touch with the latest Data Science happenings!
- Ten Signs of Data Science Maturity – free O’Reilly ebook
- May 6, 2016.
Two leading data scientists at the consulting firm Booz Allen Hamilton describe ten characteristics of a mature data science capability.
- Top April stories: 10 Essential Books for Data Enthusiast; When Deep Learning is better than SVMs or Random Forests?
- May 5, 2016.
Top 10 Essential Books for the Data Enthusiast; 10 Signs Of A Bad Data Scientist; When Does Deep Learning Work Better Than SVMs or Random Forests?; Comprehensive Guide to Learning Python for Data Science and more.
- Top KDnuggets tweets, Apr 27 – May 3: Trifecta: Python, Machine Learning, and Dueling Languages; Fun game 4 #MachineLearning newbies
- May 4, 2016.
Trifecta: #Python, #MachineLearning, + Dueling Languages; Cartoon: When #Automation Goes Too Far; #AI Speed: 2-year old #xkcd cartoon: cannot check if a photo has a bird; Removing Duplicates in #BigData.
- Top /r/MachineLearning Posts, April: New Google Machine Learning Videos, Deep Learning Book, TensorFlow Playground
- May 2, 2016.
Check out the most popular topics on Reddit's Machine Learning subreddit from April, including TensorFlow, deep learning, tutorials, self-reflection, and free books.
- Academic/Research positions in Business Analytics, Data Science, Machine Learning in April 2016
- May 2, 2016.
Academic/Research positions Analytics and Data Science in Zurich, Hatfield-UK, Paris, Ningbo-China, Tianjin-China, Melbourne, Buffalo-NY, Birmingham-UK, and Tampere-Finland.
- Top stories, Apr 24-30: How to Remove Duplicates in Large Datasets; The “Thinking” Part of “Thinking Like A Data Scientist”
- May 1, 2016.
7 Steps to Mastering Machine Learning With Python; When Does Deep Learning Work Better Than SVMs or Random Forests; How to Remove Duplicates in Large Datasets; The "Thinking" Part of "Thinking Like A Data Scientist".
