2016 Jun News, Features
All (119) | Courses, Education (6) | Meetings (12) | News, Features (21) | Opinions, Interviews, Reports (23) | Software (10) | Tutorials, Overviews (40) | Webcasts & Webinars (7)
- Top KDnuggets tweets, Jun 22-28: #Bayesian #Statistics explained in Simple English; Brexit - Jun 29, 2016.
#Bayesian #Statistics explained to Beginners in Simple English; Amazing analysis of #Brexit with #MachineLearning - it is sad; 18 Useful Mobile Apps for #DataScientist; Sharp divisions between England, #Scotland in #Brexit vote suggest future UK split.
- Top Stories, June 20-26: New Machine Learning Book, Free Draft Chapters; Machine Learning Trends & Future of A.I. - Jun 27, 2016.
New Andrew Ng Machine Learning Book Under Construction, Free Draft Chapters; Machine Learning Trends and the Future of Artificial Intelligence; Top Machine Learning Libraries for Javascript; 7 Steps to Mastering Machine Learning With Python
- Top KDnuggets tweets, Jun 15-21: Predicting UEFA Euro2016; Visual Explanation of Backprop for Neural Nets - Jun 22, 2016.
Building statistical model to predict UEFA #Euro2016; A Visual Explanation of Back Propagation Algorithm for #NeuralNetworks; Scala is the new golden child for coding and #DataScience.
- KDnuggets Blog Contest: Automated Data Science and Machine Learning - Jun 21, 2016.
KDnuggets Contest for interesting blogs about Automated Data Science and Machine Learning is over - read the 3rd, 2nd, and 1st place winners.
- Top Stories, June 13-19: A Visual Explanation of the Back Propagation Algorithm; Apache Spark Key Terms, Explained - Jun 20, 2016.
A Visual Explanation of the Back Propagation Algorithm for Neural Networks; Apache Spark Key Terms, Explained; What Big Data, Data Science, Deep Learning software goes together?; 10 Data Acquisition Strategies for Startups; 7 Steps to Mastering Machine Learning With Python
- New Andrew Ng Machine Learning Book Under Construction, Free Draft Chapters - Jun 20, 2016.
Check out the details on Andrew Ng's new book on building machine learning systems, and find out how to get your free copy of draft chapters as they are written.
- Top KDnuggets tweets, Jun 8-14: All-in-one Docker image for Deep Learning; Good Book list for Data lovers - Jun 15, 2016.
Good Book list for #Data lovers; OpenAI - a living collection of important and fun problems; All-in-one #Docker image for #DeepLearning; 10 Useful #Python #DataVisualization Libraries for Any Discipline;
- What Big Data, Data Science, Deep Learning software goes together? - Jun 14, 2016.
We analyze the associations between top Data Science tools, Commercial vs Free/Open Source, rank tools on R vs Python bias, find tools more associated with Big Data, those more associated with Deep Learning, and uncover strong regional differences.
- Machine Learning Classic: Parsimonious Binary Classification Trees - Jun 14, 2016.
Get your hands on a classic technical report outlining a three-step method of construction binary decision trees for multiple classification problems.
- Top Stories, June 6-12: Data Science of Variable Selection; R, Python Duel As Top Analytics, Data Science Software - Jun 13, 2016.
Data Science of Variable Selection; R, Python Duel As Top Analytics, Data Science Software; Big Data Business Model Maturity Index and the Internet of Things (IoT); Where are the Opportunities for Machine Learning Startups?
- PPMI Data Challenge 2016 – Help Solve Parkinsons Disease - Jun 13, 2016.
Help answer 2 key questions about Parkinson's disease and gather new insights into PD diagnosis and progression. MJFF and GE Healthcare are offering $50,000 in total prizes.
- AIG & Zurich on Machine Learning in Insurance - Jun 10, 2016.
Where and how can machine learning be practically applied by insurers? And is it worth it? Read the white paper from insurance experts at AIG and Zurich.
- Whitepaper: The Journey to Open Data Science - Jun 9, 2016.
Learn why Open Data Science is the foundation to modernizing data analytics, and ways availability, interoperability, transparency and innovation are some of the most important benefits of the ODS approach.
- Top KDnuggets tweets, Jun 1-7: “Deep” vs “Regular” Machine Learning; Introduction to Scientific Python – NumPy - Jun 8, 2016.
How to Build Your Own #DeepLearning Box; What is the Difference Between #DeepLearning and "Regular" #MachineLearning? Data Science of #Variable Selection: A Review; Why choose #Python for #MachineLearning?
- Academic/Research positions in Business Analytics, Data Science, Machine Learning in May 2016 - Jun 6, 2016.
Academic/Research positions Analytics and Data Science in Los Angeles-CA, Cardiff-Wales, and Oslo-Norway.
- R, Python Duel As Top Analytics, Data Science software – KDnuggets 2016 Software Poll Results - Jun 6, 2016.
R remains the leading tool, with 49% share, but Python grows faster and almost catches up to R. RapidMiner remains the most popular general Data Science platform. Big Data tools used by almost 40%, and Deep Learning usage doubles.
- Top Stories, May 30 – June 6: Difference Between Deep Learning and “Regular” Machine Learning; Introduction to Numpy - Jun 6, 2016.
Difference Between Deep Learning and “Regular” Machine Learning; An Introduction to Scientific Python (and a Bit of the Maths Behind It) – NumPy; How to Build Your Own Deep Learning Box; Interacting with Machine Learning - Here is Why You Should Care
- Top May stories: What software you used for Analytics, Data Mining, Data Science? - Jun 5, 2016.
Poll: What software you used for Analytics, Data Mining, Data Science? How to Explain Machine Learning to a Software Engineer; Meet 11 Big Data & Data Science Leaders on LinkedIn.
- WCAI Research Opportunity: Understanding Economic Behaviors for Financial Products – deadline June 12 - Jun 2, 2016.
The Wharton Customer Analytics Initiative is offering two research opportunities: “Understanding Past, Present, and Future Economic Behaviors for Financial Products” and “Identifying and Maintaining Great Financial Advisors". The deadline for submissions is June 12.
- Top KDnuggets tweets, May 25-31: 19 Free eBooks to learn #programming with #Python; Awesome collection of public datasets on Github - Jun 1, 2016.
Introducing Hybrid lda2vec Algorithm via Stitch Fix; #DeepLearning and Deep #Gaussian Processes - explainer; Awesome collection of public #datasets on Github; #DataScience foundations: 19 Free eBooks to learn #programming with #Python.
- Top /r/MachineLearning Posts, May: TensorFlow Tricks; Machine Learning Tutorials; Google TPUs - Jun 1, 2016.
May on /r/MachineLearning was all about tutorials, TensorFlow, Google hardware, Deep Learning machine installations, and some laughs.
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