We are in the process of writing and adding new material (compact eBooks) exclusively available to our members, and written in simple English, by world leading experts in AI, data science, and machine learning. In the upcoming months, the following will be added:

• The Machine Learning Coding Book
• Off-the-beaten-path Statistics and Machine Learning Techniques 
• Encyclopedia of Statistical Science
• Original Math, Stat and Probability Problems - with…

Summary:  This may be the golden age of deep learning but a lot can be learned by looking at where deep neural nets aren’t working yet.  This can be a guide to calming the hype.  It can also be a roadmap to future opportunities once these barriers are behind us. The full article is accessible here, below is a…

Summary: There are several approaches to reducing the cost of training data for AI, one of which is to get it for free. Here are some excellent sources.

Recently we wrote that training data (not just data in general) is the new oil. It’s the difficulty and expense of acquiring labeled training data that causes many deep learning projects to be abandoned.

It also matters a great deal just how good you want your new deep learning app to be. A 2016 study by…

Guest blog post by Zied HY. Zied is Senior Data Scientist at Capgemini Consulting. He is specialized in building predictive models utilizing both traditional statistical methods (Generalized Linear Models, Mixed Effects Models, Ridge, Lasso, etc.) and modern machine learning techniques (XGBoost, Random Forests, Kernel Methods, neural networks, etc.). Zied run some workshops for university students (ESSEC, HEC, Ecole polytechnique) interested in Data…

Summary:  The role of Analytics Translator was recently identified by McKinsey as the most important new role in analytics, and a key factor in the failure of analytic programs when the role is absent.

The role of Analytics Translator was…