Most Popular Apr 9-15

1. Why so many data scientists are leaving their jobs, by Jonny Brooks
2. Top 8 Free Must-Read Books on Deep Learning, by Dan Clark
3. Top 20 Deep Learning Papers, 2018 Edition
4. Ten Machine Learning Algorithms You Should Know to Become a Data Scientist
5. Top 20 Python AI and Machine Learning Open Source Projects
6. Don't learn Machine Learning in 24 hours
7. Top 10 Technology Trends of 2018

Most Shared Apr 9-15

1. Top 8 Free Must-Read Books on Deep Learning, by Dan Clark - Apr 10, 2018.
2. Why so many data scientists are leaving their jobs, by Jonny Brooks - Apr 09, 2018.
3. Ten Machine Learning Algorithms You Should Know to Become a Data Scientist - Apr 11, 2018.
4. Top 10 Technology Trends of 2018 - Apr 13, 2018.
5. 12 Useful Things to Know About Machine Learning - Apr 12, 2018.
6. Where Analytics, Data Science, Machine Learning Were Applied: Trends and Analysis - Apr 09, 2018.
7. Implementing Deep Learning Methods and Feature Engineering for Text Data: The Skip-gram Model - Apr 10, 2018.

Previous weeks top stories:

• Apr 2-8: Top 20 Deep Learning Papers, 2018 Edition; How Do I Get My First Data Science Job?
• Mar 26 - Apr 1: Text Data Preprocessing: A Walkthrough in Python; A Weird Introduction to Deep Learning
• Mar 19-25: 5 Things You Need to Know about Sentiment Analysis and Classification; Top 12 Essential Command Line Tools for Data Scientists
• Mar 12-18: Will GDPR Make Machine Learning Illegal?; 5 Things You Need to Know about Big Data
• Mar 5-11: The Two Sides of Getting a Job as a Data Scientist; Time Series for Dummies – The 3 Step Process
• Feb 26 - Mar 4: Introduction to Functional Programming in Python; A Tour of The Top 10 Algorithms for Machine Learning Newbies
• Feb 19-25: Top 20 Python AI and Machine Learning Open Source Projects; Deep Learning Development with Google Colab, TensorFlow, Keras & PyTorch

2018 Top stories each month

• March: Will GDPR Make Machine Learning Illegal?
• February: Neural network AI is simple. So... Stop pretending you are a genius
• January: Docker for Data Science; Top 10 TED Talks for Data Scientists and Machine Learning Engineers

Top stories in 2017

• 10 Free Must-Read Books for Machine Learning and Data Science; Python overtakes R, becomes the leader in Data Science, Machine Learning platforms; Top 10 Machine Learning Algorithms for Beginners; 30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets

2017 Top stories each month

• December: Computer Vision by Andrew Ng – 11 Lessons Learned; Top Data Science and Machine Learning Methods Used in 2017
• November: The 10 Statistical Techniques Data Scientists Need to Master
• October: Top 10 Machine Learning Algorithms for Beginners
• September: 30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets
• August: Python overtakes R, becomes the leader in Data Science, Machine Learning platforms
• July: The 4 Types of Data Analytics
• June: Top 15 Python Libraries for Data Science in 2017
• 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

• 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