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Data Science Method Framework, guides the selection of the appropriate method for the biz problem/goal

WebBook by Ben Webber (Data Scientist at Zynga) about creating a data science discipline at a startup.

Book: Broad and less technical treatment of key topics. Each concept is explained with case studies in R

Book:  For beginners and intermediate professionals who would like to learn data analytics without the mathematics

WebBook: Balances theory and experiment, showing how to link them intimately together

Reference for SQL Commands, a Complete List (w/ Examples) put together by Dataquest 

Book: With each problem, evaluate conventional methods and then introduce a method based on sparsity

Book: Not for beginners. The world of machine learning seen through the lens of optimization

WebBook: Elon Musk says this is the most comprehensive book on deep learning covering almost every facet

Great list of cheat sheets but also a visual map on areas and topics in Data Science for your learning journey.

Book: Introduction to the subject with infographics and a guide on how to choose the right technique

WebBook: Primer on the mathematical background for data mining and  statistical machine learning

Book:  Written by the Keras creator and Google AI Researcher Francois Chollet.