Author: Indranath Chatterjee

Machine Learning and Its Application: A Quick Guide for Beginners

eBook: US $69 Special Offer (PDF + Printed Copy): US $117
Printed Copy: US $83
Library License: US $276
ISBN: 978-1-68108-941-6 (Print)
ISBN: 978-1-68108-940-9 (Online)
Year of Publication: 2021
DOI: 10.2174/97816810894091210101
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Machine Learning and Its Application: A Quick Guide for Beginners aims to cover most of the core topics required for study in machine learning curricula included in university and college courses. The textbook introduces readers to central concepts in machine learning and artificial intelligence, which include the types of machine learning algorithms and the statistical knowledge required for devising relevant computer algorithms. The book also covers advanced topics such as deep learning and feature engineering.

Key features:

  • - 8 organized chapters on core concepts of machine learning for learners
  • - Accessible text for beginners unfamiliar with complex mathematical concepts
  • - Introductory topics are included, including supervised learning, unsupervised learning, reinforcement learning and predictive statistics
  • - Advanced topics such as deep learning and feature engineering provide additional information
  • - Introduces readers to python programming with examples of code for understanding and practice
  • - Includes a summary of the text and a dedicated section for references

Machine Learning and Its Application: A Quick Guide for Beginners is an essential book for students and learners who want to understand the basics of machine learning and equip themselves with the knowledge to write algorithms for intelligent data processing applications.


Over the past two decades, the evolution of Machine Learning has risen to a great extent. With the invention of Artificial Intelligence, things were getting more comfortable and accessible. Artificial intelligence needs a system to be fed with pre-defined conditional statements to perform some tasks on behalf of human beings. Gradually human needs a more stable and autonomous system that can learn on its own. There comes a lack of another technology that drastically changes the concept of artificial intelligence. With the invention of machine learning, advancements are going on every single day. With ever-increasing data sources and automated computation, technologies based on machine learning are coming alive very often.

The purpose of writing 'another book on machine learning is always a challenging task to attract the reader's attention. Machine learning is the most discussed topic of this decade and for a few more decades. The basic knowledge of machine learning is very needed. Most people are unaware of the fundamental theories and applications of machine learning.

Among many books available in the market on this topic, this book targets reaching all the corners of the reading society. From naïve learners to professional machine learning experts will find this book handy and helpful for everyday application. Most books are written in challenging mathematical perspectives, which pose incomprehensibility for most readers, especially students and industry engineers.

This book aims to cover most of the Machine Learning curriculum prescribed in most of the top universities. It also covers advanced topics like Deep Learning and Feature Engineering. This book's added feature is the entire chapter on realworld machine learning applications using Python programming, which will be truly beneficial for all the researchers and engineers, with open-ended ideas on new problems and their solutions in a Pythonic way.

This book is written effortlessly and straightforwardly with enriched theories and more minor mathematical complications, but more easily comprehensive application aspects. In every chapter, topics are described in such a way, keeping in mind readers from all sections. Every topic and subtopic is described with examples and Python code snippets for a more accessible explanation. The chapters are presented with a well-explained illustration and flowchart for a better understanding of the topic. Thus, this book on machine learning will surely catch the beginners' attention in the Machine Learning domain. The audience will include, University students, Young Researchers, Ph.D. students, Professors, and software engineers who want to gain knowledge in Machine learning from scratch. I believe this book will be in demand of most of the University libraries and bookstores.


Not applicable.


A single author entirely writes this book. So, the conflict of interest does not apply to this book.


Writing a book is more exciting than I anticipated and more rewarding than I could have dreamed. Nothing would have been imaginable without the strength and ability bestowed upon me by the Almighty God because I would not be able to do anything without Him. I want to thank and express my gratitude to my closest family and friends.

I am eternally grateful to my family for their unwavering mental support and persistent encouragement, which has aided me in accomplishing this book in a timely and efficient manner. My family members, Mr. Narendranath Chatterjee, Mrs. Rupasree Chatterjee, Mr. Rudranath Chatterjee, and Ms. Soumi Chatterjee, deserve special thanks for sticking by my side throughout the duration. Love to you all!

I want to express intense gratitude to my dearest people, Mr. Ajay Kumar and Mrs. Rekha Devi, for their unceasing impetus and motivation. A huge cheer to you!

I am eternally grateful to my professor, friend, and charioteer, Prof. Naveen Kumar, whose insightful guidance and wisdom drove me to refine my belief to evolve the best in me.

A special thanks to my students, without whose contribution, this book may not look so magnificent as it is now. I am grateful to my dearest student Ms. Videsha Bansal for her continuous support and contribution in organizing the contents. I am very thankful to my beloved student at Tongmyong University, Mr. Sunghyun Kim, for his contribution and support in the programming section of the book. I am also thankful to my beloved research student Ms. Lea Baumgärtner for her encouragement and assistance in the programming section of the book. A special thanks to my student Mr. Sajal Jain for supporting me in giving the professional touch to the figues and diagrams.

I am very much grateful to Prof. Pamela Douglas from University of California, Los Angeles for reviewing the book and giving her valuable comments to improve the overall content of this book. I am also thankful to all my friends and colleagues at Tongmyong University for their support and good wishes. I am grateful to Mrs. Humaira Hashmi, Editorial Manager of Bentham Science Publishers, for her continuous support during the period.

Indranath Chatterjee Ph. D.
Department of Computer Engineering
Tongmyong University
South Korea