Advances in the field of machine learning are driving progress more widely in AI. But many terms and concepts will seem incomprehensible to the intelligent outsider, the beginner, and even the former student of AI returning to a transformed discipline after years away. We hope this helps you better understand AI, the software used to build it, and what is at stake in its development.
This book is a beginner’s guide to important topics in AI, machine learning, and deep learning.
Introduction to fundamental machine learning and deep learning algorithms.
An assessible walkthrough of the mechanics of machine learning.
An overview of widely-used architectures that you will encounter in the wild and perhaps consider for your use case.
An overview of bleeding-edge architectures that are driving state-of-the-art advancements in AI.
A brief rundown of machine learning workflows, datasets, evaluation metrics, and frameworks.