Thank you for purchasing the MEAP for Machine Learning Algorithms in Depth. This book will take you on a journey from mathematical derivation to software implementation of some of the most intriguing algorithms in ML.
This book dives into the design of ML algorithms from scratch. Throughout the book, you will develop mathematical intuition for classic and modern ML algorithms, learn the fundamentals of Bayesian inference and deep learning, as well as the data structures and algorithmic paradigms in ML.
Understanding ML algorithms from scratch will help you choose the right algorithm for the task, explain the results, troubleshoot advanced problems, extend an algorithm to a new application, and improve performance of existing algorithms.
Some of the prerequisites for reading this book include basic level of programming in Python and intermediate level of understanding of linear algebra, applied probability and multivariate calculus.
My goal in writing this book is to distill the science of ML and present it in a way that will convey intuition and inspire the reader to self-learn, innovate and advance the field. Your input is important. I’d like to encourage you to post questions and comments in the liveBook discussion forum to help improve presentation of the material.
Thank you again for your interest and welcome to the world of ML algorithms!
— Vadim Smolyakov