Essential Mathematics for Machine Learning!!
Are you searching over the web for one complete book for clear understanding of the mathematical concepts on your machine learning journey?
You will be surprised to know about this free mathematics book that would resolve all your confusions points on basic mathematics related to machine learning.
Here is the book! Mathematics for Machine Learning
The book is published by Cambridge University Press (Edition April 2020).
The above book would cover the essential mathematical concepts that are solely used for machine learning purposes. Each idea conveyed here is very clear and concise. There are no advanced or complex methodologies discussed here. So even if you are just a beginner or an experienced professional who is looking to brush up your necessary mathematical skills could plunge into this definitive guide!
This book is divided into two parts. The first part is all about mathematical foundations, and the second part is about example, machine learning algorithms that use the mathematical foundations.
Now we shall have a look into the contents of this book!
Table of Contents
Part I: Mathematical Foundations

Introduction and Motivation

Linear Algebra

Analytic Geometry

Matrix Decompositions

Vector Calculus

Probability and Distribution

Continuous Optimization
Part II: Central Machine Learning Problems

When Models Meet Data

Linear Regression

Dimensionality Reduction with Principal Component Analysis

Density Estimation with Gaussian Mixture Models

Classification with Support Vector Machines
Yup, these are the topics covered here for your understanding.
This book is one solid gold of value for every machine learning aspirant, which comes in absolute free of cost. Do make the best use of it!
You could download the PDF version instantly over here!