Most Popular June 11-17

1. Data Lake – the evolution of data processing, by Nebojsa Arezina
2. 5 Machine Learning Projects You Should Not Overlook, June 2018, by Matthew Mayo
3. 10 More Free Must-Read Books for Machine Learning and Data Science
4. A Beginners Guide to the Data Science Pipeline
5. The 6 components of Open-Source Data Science/ Machine Learning Ecosystem; Did Python declare victory over R?
6. Python eats away at R: Top Software for Analytics, Data Science, Machine Learning in 2018: Trends and Analysis
7. Command Line Tricks For Data Scientists

Most Shared June 11-17

1. Data Lake – the evolution of data processing, by Nebojsa Arezina - Jun 14, 2018.
2. Generating Text with RNNs in 4 Lines of Code, by Matthew Mayo - Jun 14, 2018.
3. Cartoon: FIFA World Cup Football and Machine Learning - Jun 16, 2018.
4. The What, Where and How of Data for Data Science - Jun 12, 2018.
5. 5 Machine Learning Projects You Should Not Overlook, June 2018 - Jun 12, 2018.
6. How To Create Natural Language Semantic Search For Arbitrary Objects With Deep Learning - Jun 13, 2018.
7. IoT on AWS: Machine Learning Models and Dashboards from Sensor Data - Jun 15, 2018.

Previous weeks top stories:

• Jun 4-10: Did Python declare victory over R?; The Keras 4 Step Workflow
• May 28 - Jun 3: 10 More Free Must-Read Books for Machine Learning and Data Science; A Beginners Guide to the Data Science Pipeline
• May 21-27: Python eats away at R: Top Software for Analytics & Data Science; ETL vs ELT: Considering the Advancement of Data Warehouses
• May 14-20: Data Science vs Machine Learning vs Data Analytics vs Business Analytics; Implement a YOLO Object Detector from Scratch in PyTorch
• May 7-13: 2018 KDnuggets Analytics, Data Mining, Data Science, Machine Learning Software Poll; WTF is a Tensor?!?
• Apr 30 - May 6: Boost your data science skills. Learn linear algebra.; Operational Machine Learning: Seven Considerations for Successful MLOps
• Apr 23-29: Blockchain Explained in 7 Python Functions; Building Convolutional Neural Network using NumPy from Scratch

2018 Top stories each month

• May: Python eats away at R: Top Software for Analytics, Data Science, Machine Learning in 2018; Data Science vs Machine Learning vs Data Analytics vs Business Analytics
• April: Why so many data scientists are leaving their jobs? 7 Books to Grasp Math Foundations of Data Science and Machine Learning
• 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