Top 10 Books for Machine Learning you should Read

Machine learning has given humanity the energy to handle tasks in an automatic way. It lets us improve things that we already do by studying a continuous stream of data related to that same task. Machine learning has a full collection of applications that belongs to various fields, ranging from space research to digital marketing. Machine learning also forms the base of artificial intelligence.

It is the best time to learn a machine learning course. Machine learning is a difficult area but that doesn’t mean that it can’t be understood easily.

To help you get a better understanding of the Machine Learning KVCH has mentioned several books for your reading.

1. The Hundred-Page Machine Learning Book.

# This is written by Andriy Burkov.

# The book is written in an easy-to-understand way, the machine learning book is accepted by respected leaders and various Directors of Research who say that it is the best book for Machine Learning to start with.

# After a careful reading of the book, you will be able to build and recognize difficult AI systems, clear and ML-based interviews, and even start your very own ml-based company.

2. Machine Learning

# Machine Learning by Tom M. Mitchell is a perfect book for getting started with machine learning. It offers a broad summary of machine learning theorems with summaries of the respective algorithms. This book is full of examples and case studies to relieve the tension in a reader’s struggle for learning and understanding ml algorithms.

3. Learning from Data: A Short Course

# This is written by-Yaser Abu Mostafa, Malik Magdon-Ismail, and Hsuan-Tien Lin

# Instead of giving knowledge about the various advanced ideas about machine learning, the book prepares its readers to better understand the difficult machine learning ideas.

4. Understanding Machine Learning

# Written by-Shai Shalev-Shwartz and Shai Ben-David

# This book gives a proper introduction to machine learning. The book mentions the basic theories and algorithmic paradigms of machine learning, and mathematical origins.

5. Machine learning for Dummies

# Written by-John Paul Mueller and Luca Massaron

# This book aims to make the readers aware of the basic concepts and theories easily about machine learning. Also, the book points to the practical, real-world applications of machine learning.

6. Python Machine Learning

# Written by-Leonard Eddison

# This book mentions the basics of machine learning as well as its importance in the digital area. The book also discusses the different branches of machine learning and its large variety of applications.

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7. Introduction to Machine Learning with Python: A Guide for Data Scientists

# Written by- Andreas C. Müller & Sarah Guido

# Are you a data scientist master in using Python and interested in learning ML? Then this book is a suitable book for you to pick up and kick start your machine learning journey.

# This book will teach you various practical means of building your very own machine learning solutions.

8. Machine learning with Tensorflow

# Written by-Nishant Shukla

# This book explains the ml basics with common classification, clustering, and prediction algorithms. The book even discusses machine learning concepts in-depth and makes the readers prepared for any kind of machine learning task using the free and open-source TensorFlow library.

9. Machine learning in Action

# Written by-Peter Harrington

# This is yet another excellent machine learning book liked by a variety of people ranging from undergraduates to professionals. It not only notes machine learning techniques but the concepts underlying them as well as in a thoroughly-explained means.

10. Machine learning for Absolute Beginners

# Written by-Oliver Theobald

# Have no previous experience and direction in machine learning? But still, want to learn it? Then you should read this book. No coding or mathematical experience is required to benefit from this machine learning book.

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