Asjadh Muzammil
About The E-Book
- Title – Mathematics for Machine Learning
- Author – Marc Peter Deisenroth, A. Aldo Faisal and Cheng Soon Ong
- Total Pages – 417 Pages
- Total Chapters – 12 Chapters
- E-Book Size – 16 MBs
The fundamental mathematical tools to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to learn mathematics efficiently. This self contained textbook bridges the gap between mathematical and machine learning texts, introducing
mathematical concepts with a minimum of prerequisites.
It uses these concepts to derive four main machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. These derivations provide a starting point for machine learning texts for students and others with a mathematical background. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes work examples and exercises to test understanding. Programming tutorials are offered on the book’s website.
Book Contents
- Introduction and Motivation
- Linear Algebra
- Analytic Geometry
- Matrix Decompositions
- Vector Calculus
- And More
Machine Learning – Example Pages
Who can Read This?
As applications of machine learning become widespread in society, we
believe that everybody should have some understanding of its underlying principles. This book is written in an academic mathematical style, which
enables us to be precise about the concepts behind machine learning. We
encourage readers unfamiliar with this seemingly terse style to persevere
and keep the goals of each topic in mind. We sprinkle comments and
remarks throughout the text, hoping it provides valuable guidance for the big picture.
The book assumes the reader to have mathematical knowledge commonly
Thank You !!
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