• Title: Machine Learning from Scratch
• Author(s) Danny Friedman
• Publisher: GitHub;
• Paperback: N/A
• eBook: HTML, PDF, Jupyter Book
• Language: English
• ISBN-10: N/A
• ISBN-13: N/A
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Book Description

This book covers the building blocks of the most common methods in machine learning. This set of methods is like a toolbox for machine learning engineers. Those entering the field of machine learning should feel comfortable with this toolbox so they have the right tool for a variety of tasks. Each chapter in this book corresponds to a single machine learning method or group of methods. In other words, each chapter focuses on a single tool within the ML toolbox.

The purpose of this book is to provide those derivations. Each chapter is broken into three sections. The concept sections introduce the methods conceptually and derive their results mathematically. The construction sections show how to construct the methods from scratch using Python. The implementation sections demonstrate how to apply the methods using packages in Python like scikit-learn, statsmodels, and tensorflow.

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• From Scratch
• Machine Learning
• Neural Networks and Deep Learning
• Artificial Intelligence
• Data Analysis and Data Mining

• Machine Learning from Scratch (Danny Friedman)
• The Mirror Site (1) - PDF
• The Mirror Site (2) - PDF

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