Top Stories
Most Popular Jun 12-18
- Top 15 Python Libraries for Data Science in 2017, by Igor Bobriakov
- 6 Interesting Things You Can Do with Python on Facebook Data, by Nour Galaby
- Deep Learning Papers Reading Roadmap
- The 10 Algorithms Machine Learning Engineers Need to Know
- Data Scientist: Learn the Skills you need for free
- 10 Free Must-Read Books for Machine Learning and Data Science
- Is Regression Analysis Really Machine Learning?
Most Shared Jun 12-18
- Deep Learning Papers Reading Roadmap, by Flood Sung - Jun 13, 2017.
- Top 15 Python Libraries for Data Science in 2017, by Igor Bobriakov - Jun 13, 2017.
- The Practical Importance of Feature Selection - Jun 12, 2017.
- Understanding Deep Learning Requires Re-thinking Generalization - Jun 16, 2017.
- K-means Clustering with Tableau – Call Detail Records Example - Jun 16, 2017.
- 7 Ways to Get High-Quality Labeled Training Data at Low Cost - Jun 13, 2017.
- Medical Image Analysis with Deep Learning, Part 3 - Jun 15, 2017.
Previous weeks top stories:
- Jun 5-11: Is Regression Analysis Really Machine Learning?; 6 Interesting Things You Can Do with Python on Facebook Data
- May 29-Jun 4: Machine Learning Workflows in Python from Scratch; Machine Learning Algorithms Cheat Sheet
- May 22-28: Analytics, Data Science, Machine Learning Software Poll Results; Machine Learning Crash Course
- May 15-21: Getting Into Data Science: What You Need to Know; The Best Python Packages for Data Science
- May 8-14: Annual KDnuggets Data Science Software Poll; Using Deep Learning To Extract Knowledge From Job Descriptions
- May 1-7: How to Learn Machine Learning in 10 Days; Deep Learning – Past, Present, and Future
- Apr 24-30: Guerrilla Guide to Machine Learning with Python; Understand the Gradient Descent Algorithm
2017 Top stories each month
- May: KDnuggets Poll: Software for Analytics, Data Science, Machine Learning; How to Learn Machine Learning in 10 Days
- April: 10 Free Must-Read Books for Machine Learning and Data Science
- 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
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
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
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