Every month we scour the internet seeking out free eBooks to help you on your educational journey, and this month has been no different.
I hope these books prove to be a valuable resource to you and that you will visit regularly (and invite your friends too).
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This month, we have The Data Science Handbook, a Python programming book about how to think like a data scientist and one about Artificial Intelligence. They're all FREE, so no excuses why you shouldn't give them a go...
by Carl Shan, Henry Wang, William Chen and Max Song
The Data Science Handbook is a compilation of in-depth interviews with 25 remarkable data scientists, where they share their insights, stories, and advice.
These 25 data scientists hail from a wide selection of backgrounds, disciplines, and industries.
Some of them, like DJ Patil and Hilary Mason, were part of the trailblazing wave of data scientists who catapulted the field into national attention.
Others are at the start of their careers, such as Clare Corthell, who made her own path to data science by creating the Open Source Data Science Masters, a self-guided curriculum built on freely available internet resources.
by Allen Downey
Think Python is an introduction to Python programming for beginners.
It starts with basic concepts of programming, and is carefully designed to define all terms when they are first used and to develop each new concept in a logical progression.
Larger pieces, like recursion and object-oriented programming are divided into a sequence of smaller steps and introduced over the course of several chapters.
by David Poole and Alan Macworth
This is a book about the science of artificial intelligence (AI).
It presents artificial intelligence as the study of the design of intelligent computational agents. The book is structured as a textbook, but it is accessible to a wide audience of professionals and researchers. In the last decades we have witnessed the emergence of artificial intelligence as a serious science and engineering discipline. This book provides the first accessible synthesis of the field aimed at undergraduate and graduate students. It provides a coherent vision of the foundations of the field as it is today. It aims to provide that synthesis as an integrated science, in terms of a multi-dimensional design space that has been partially explored.
As with any science worth its salt, artificial intelligence has a coherent, formal theory and a rambunctious experimental wing. The book balances theory and experiment, showing how to link them intimately together. It develops the science of AI together with its engineering applications.