Machine Learning from Scratch

Dive into the principles and algorithms of machine learning with "Machine Learning From Scratch" - a comprehensive guide for beginners and experienced practitioners alike.

Introduction

Machine Learning from Scratch is a comprehensive guide to understanding the principles and algorithms of machine learning, written by Danny Friedman. The book covers topics such as supervised learning, unsupervised learning, and deep learning, making it a valuable resource for beginners and experienced practitioners alike.

Highlights

• Covers the building blocks of the most common methods in machine learning
• Provides derivations of machine learning algorithms from scratch, both in theory and in code
• Focuses on the bare bones of machine learning algorithms to help readers construct them independently
• Includes an appendix that reviews the math, probability, and common machine learning methods needed to understand the content

Recommendation

This book is recommended for readers looking to learn new machine learning algorithms or understand algorithms at a deeper level. It is particularly helpful for those with practice in basic modeling who are interested in seeing machine learning algorithms derived from start to finish.