Tradewind AI Knowledge Base & Library
2 BOOKS IN 1: ARTIFICIAL INTELLIGENCE A MODERN APPROACH & ARTIFICIAL INTELLIGENCE BUSINESS APPLICATIONS BY CHRIS BAKER
Learn the potential consequences of Artificial Intelligence and how it will shape the world around us in the coming decades! Become familiar with how Artificial Intelligence aims to aid human cognitive limitations and how it is possible that in the future, the AI that humans create becomes inconceivable to humans themselves. And once you have an understanding of what AI is, you can move forward in your journey to create better informed industry-level business AI applications.
THE MASTER ALGORITHM
This book provides a wider framework than just deep learning, which is the hot thing now. Two things to bear in mind: People should know about the different tribes, as the author calls them, and they should also understand that most solutions are going to be ensemble systems, meaning it's not going to be one-tribe-takes-all. It's going to be a combination of several.
BUILDING ARTIFICIAL INTELLIGENCE WE CAN TRUST BY GARY MARCUS AND ERNEST DAVIS
I see this book as being kind of a shot across the bow of the deep learning/connectionist camp, which has sort of taken over the discussion around artificial intelligence. In fact, the leading connectionist conference, NeurIPS, just recently took place. There are several different traditional ML camps; connectionism is neural networks — same idea.
AI FOR PEOPLE AND BUSINESS
FOR EXECUTIVES, MANAGERS AND NON-TECHNICAL FOLKS BY ALEX CASTROUNIS
It’s becoming imperative for business leaders to understand artificial intelligence and machine learning at an appropriate level in order to build great data-centric products and solutions.
MACHINE LEARNING YEARNING
TECHNICAL STRATEGY FOR AI ENGINEERS, IN THE ERA OF DEEP LEARNING BY ANDREW NG
A great book for practitioners in its broad coverage of machine learning and its application to artificial intelligence. Written in a much more how-to- or cookbook-style approach than that book. It's sort of like, if you want to do this, this is how you do it; if you want to do that, this is how you do that.