Most Popular Apr 17-23
- 10 Free Must-Read Books for Machine Learning and Data Science, by Matthew Mayo
- Forrester vs Gartner on Data Science Platforms and Machine Learning Solutions, by Gregory Piatetsky
- New Online Data Science Tracks for 2017
- Awesome Deep Learning: Most Cited Deep Learning Papers
- The 10 Algorithms Machine Learning Engineers Need to Know
- Data Science for the Layman (No Math Added)
- Top mistakes data scientists make when dealing with business people
Most Shared Apr 17-23
- Awesome Deep Learning: Most Cited Deep Learning Papers, by Terry Taewoong Um - Apr 21, 2017.
- Data Science for the Layman (No Math Added), by Annalyn Ng and Kenneth Soo - Apr 20, 2017.
- The Value of Exploratory Data Analysis - Apr 20, 2017.
- The dynamics between AI and IoT - Apr 18, 2017.
- Time Series Analysis with Generalized Additive Models - Apr 18, 2017.
- How Big Data Helps Today’s Airlines Operate - Apr 19, 2017.
- Difference Between Big Data and Internet of Things - Apr 21, 2017.
Previous weeks top stories:
- Apr 10-16: 10 Free Machine Learning & Data Science Books; 5 Machine Learning Projects You Can’t Overlook
- Apr 3-9: Top 20 Machine Learning & Deep Learning Research Papers; Brief History of Artificial Intelligence
- Mar 27-Apr 2: Standardization and Specialization in Data Science; What is Structural Equation Modeling?
- Mar 20-26: What Is Data Science, What Does a Data Scientist Do?; The Most Underutilized Function in SQL
- Mar 13-19: 6 Business Concepts Data Science Unicorns Need; 50 Companies Leading The AI Revolution, Detailed
- Mar 6-12: What Makes a Good Data Science Visualization; A Ridiculously Specific Guide to Getting a Data Science Job
- Feb 27-Mar 5: 7 More Steps to Mastering Machine Learning With Python; An Overview of Python Deep Learning Frameworks
2017 Top stories each month
- March: 7 More Steps to Mastering Machine Learning With Python; 50 Companies Leading The AI Revolution, Detailed
- February: 17 More Must-Know Data Science Interview Questions and Answers; 5 Career Paths in Big Data and Data Science, Explained
- January: The Most Popular Language For Machine Learning and Data Science Is ...
Top stories in 2016
- 21 Must-Know Data Science Interview Questions and Answers;
10 Algorithms Machine Learning Engineers Need to Know;
Software used for Analytics, Data Science, Machine Learning projects;
Top Algorithms and Methods Used by Data Scientists
2016 Top stories each month
- December: 50+ Data Science, Machine Learning Cheat Sheets; Machine Learning/AI: Main 2016 Developments, Key 2017 Trends
- November: Trump, Failure of Prediction, and Lessons for Data Scientists
- October: 5 EBooks to Read Before Getting into A Machine Learning Career; Top 10 Data Science Videos on YouTube
- September: Top Algorithms and Methods Used by Data Scientists
- August: The 10 Algorithms Machine Learning Engineers Need to Know; How to Become a Data Scientist
- July: Bayesian Machine Learning, Explained; Why Big Data is in Trouble: They Forgot About Applied Statistics
- June: The Difference Deep Learning and "Regular" Machine Learning? R, Python duel as top Data Science tools
- May: Poll: What software you used for Analytics, Data Mining, Data Science? How to Explain Machine Learning to a Software Engineer
- April: 10 Essential Books for Data Enthusiast; When Deep Learning is better than SVMs or Random Forests?
- March: R Learning Path: From beginner to expert in 7 steps; R or Python? Consider learning both
- February: 21 Must-Know Data Science Interview Q&A; Gartner 2016 MQ for Advanced Analytics: gainers and losers
- January: 20 Questions to Detect Fake Data Scientists, Machine Intelligence vs. Machine Learning vs. Deep Learning vs. AI
Top stories in 2015
- R vs Python for Data Science: The Winner is ...;
60+ Free Books on Big Data, Data Science, Data Mining
Top 20 Python Machine Learning Open Source Projects;
50+ Data Science and Machine Learning Cheat Sheets.
2015 Top stories each month
- December: Top 10 Machine Learning Projects on Github; 50 Useful Machine Learning, Prediction APIs
- November: TensorFlow Disappoints - Google Deep Learning falls shallow; 5 Best Machine Learning APIs for Data Science
- October: Top 5 arXiv Deep Learning Papers, Explained; R vs Python: head to head data analysis
- September: 60+ Free Books on Big Data, Data Science; The one language a Data Scientist must master
- August: How to become a Data Scientist for Free; Data is Ugly - Tales of Data Cleaning
- July: 50+ Data Science and Machine Learning Cheat Sheets; Deep Learning and the Triumph of Empiricism
- June: Top 20 Python Machine Learning Projects; Which Big Data, Data Mining Tools go together?
- May: Most popular Predictive Analytics, Data Mining, Data Science software; R vs Python
- April: Awesome Public Datasets on GitHub; Forrester Wave Big Data Predictive Analytics - Gainers and Losers
- March: 7 common Machine Learning mistakes; Deep Learning for Text Understanding from Scratch
- February: 10 things statistics taught about big data; Gartner Analytics MQ: gainers and losers
- January: (Deep Learning Deep Flaws) Deep Flaws; Research Leaders on key trends, papers
Top stories in 2014
- Does Deep Learning Have Deep Flaws?
Is Data Scientist the right career path for you?
Four main languages for Analytics, Data Mining, Data Science; Cartoon: Big Data and World Cup Football
2014 Top stories by month
- December: If programming languages were vehicles; Cartoon: Unexpected Data Science Recommendations
- November: 9 Must-Have Skills for a Data Scientist; IBM Watson Analytics replacing a data scientist?
- October: Ebola Analytics and Data Science Lessons; Will Deep Learning take over Machine Learning?
- September: Data Science is mainly a Human Science; Hiring Data Scientists: What to look for?
- August: Four main languages for Analytics, Data Mining, Data Science
- July: Cartoon: Facebook data science experiment and Cats; Data Mining/Data Science "Nobel Prize"
- June: Does Deep Learning Have Deep Flaws? Cartoon: Big Data and World Cup
- May: New Poll - Analytics, Data Mining Software; Data Science Cheat Sheets
- April: Apache Spark, the hot new trend in Big Data; Data Analytics Handbook, free download
- March: Machine Learning in 7 Pictures; How Many Data Scientists?
- February: 3 Ways to test the accuracy; Exclusive Interview with Yann LeCun; One Page R
- January: Tutorial: Data Science in Python; Learning from Data, Caltech free online course