Top stories for Jan 24-30: 7 Common Data Science Mistakes; Businesses Will Need 1M Data Scientists by 2018
Tags: Top stories
20 Questions to Detect Fake Data Scientists; TensorFlow Disappoints - Google Deep Learning falls shallow; 7 Common Data Science Mistakes and How to Avoid Them; Businesses Will Need One Million Data Scientists by 2018.
Most viewed stories overall
-
20 Questions to Detect Fake Data Scientists
- TensorFlow Disappoints - Google Deep Learning falls shallow
- R vs Python for Data Science: The Winner is ...
- 7 Steps to Mastering Machine Learning With Python
- 9 Must-Have Skills You Need to Become a Data Scientist
- 7 Common Data Science Mistakes and How to Avoid Them
- Top 10 Data Analysis Tools for Business
20 Questions to Detect Fake Data ScientistsMost shared
- 7 Common Data Science Mistakes and How to Avoid Them - Jan 26, 2016.
- Businesses Will Need One Million Data Scientists by 2018 - Jan 28, 2016.
- Modern Data Science and Evolution of BI - Jan 26, 2016.
- Sentiment Analysis & Predictive Analytics for trading. Avoid this systematic mistake - Jan 25, 2016.
- Implementing Your Own k-Nearest Neighbour Algorithm Using Python - Jan 27, 2016.
- Google Launches Deep Learning with TensorFlow MOOC - Jan 26, 2016.
- Spark and the Remorseless Recrystallization of the Open Source Analytics Ecosystem - Jan 23, 2016.
7 Common Data Science Mistakes and How to Avoid ThemMost viewed recent stories
- 20 Questions to Detect Fake Data Scientists
- 7 Common Data Science Mistakes and How to Avoid Them
- Learning to Code Neural Networks
- What Is Machine Intelligence Vs. Machine Learning Vs. Deep Learning Vs. Artificial Intelligence (AI)?
- Anthony Goldbloom gives you the Secret to winning Kaggle competitions
- Google Launches Deep Learning with TensorFlow MOOC
- Yahoo Releases the Largest-ever Machine Learning Dataset for Researcher
