A rigorous overview of data science tools in Python, combined with an introduction to several machine learning techniques using the sci-kit learn library.
As someone that has approached learning data science and programming on a project-by-project basis, it was wonderfully enlightening to see the author dive deep into the syntax, and reasoning behind libraries such as NumPy, Pandas, and Matplotlib. The chapter on machine learning is surprisingly hefty considering how much has come prior to it.
I read this book for free on the author’s GitHub however I will be going back and purchasing it, as it truly is a handbook. I have already gone back and referred to work in this book on several projects, and I know that I’ll be using it in the future to flick through to refresh my ideas, or think about how I would structure my own code.