Dear friends,

Welcome to the Feb 23rd edition of The Sunday Briefing. 

Today we have several exciting news. First off, we are proud to announce that the second blog post covering Judea Pearls's Causal Inference in Statistics - A Primer (affiliate link) a short and to the point introduction to Causality.  We invite you to follow along and send use your comments and suggestions. Naturally, having a physical copy of the book is not a requirement, but it's highly recommended as it makes it easier to follow along.

Furthermore, we are happy to invite you to a free full day tutorial on March 7. The topic will be  Time Series Modeling: ML and Deep Learning Approaches with Python and it will be hosted by good folks over at the NYC offices of Farfetch  and organized by the new NYC URGs and Allies in Data Science Meetup and NYC PyLadies.

Onwards with our regularly scheduled content. This week we have posts covering M3DB a 
  a distributed timeseries database from the engineer at Uber, a set of wonderful 120 year old visualizations on racism, inequality, and black life in America, unfortunately and evergreen topic and an overview of word Embeddings from the Ground Up.

On the academic front,  we have an approach to improve likelihood-free inference on implict models, a survey on Deep Learning for Financial Applications and a new dataset of speech patterns obtained from TV Series. 

Finally, in the video of the week Craig Sakuma presents his Intro to Python for Data Science from ODSC West 2015

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Semper discentes,

The D4S team