Supervised Machine Learning, Subir Gupta (9786207844548) — Readings Books
 
Paperback

Supervised Machine Learning

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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

The book "Supervised Machine Learning: A Comprehensive Guide" by Dr. Subir Gupta aims to provide an in-depth understanding of supervised machine learning algorithms. It targets students, professionals, and researchers, offering clear explanations and practical applications. The book is divided into three main sections: an introduction to the fundamental concepts and types of supervised learning, a detailed exploration of regression algorithms, and an extensive examination of classification algorithms. Each algorithm is explained with definitions, practical uses, pseudocode, and discussions of their limitations. The guide is designed to be a valuable resource for anyone looking to apply machine learning techniques effectively to solve real-world problems.

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Format
Paperback
Publisher
LAP Lambert Academic Publishing
Date
26 August 2024
Pages
56
ISBN
9786207844548

This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

The book "Supervised Machine Learning: A Comprehensive Guide" by Dr. Subir Gupta aims to provide an in-depth understanding of supervised machine learning algorithms. It targets students, professionals, and researchers, offering clear explanations and practical applications. The book is divided into three main sections: an introduction to the fundamental concepts and types of supervised learning, a detailed exploration of regression algorithms, and an extensive examination of classification algorithms. Each algorithm is explained with definitions, practical uses, pseudocode, and discussions of their limitations. The guide is designed to be a valuable resource for anyone looking to apply machine learning techniques effectively to solve real-world problems.

Read More
Format
Paperback
Publisher
LAP Lambert Academic Publishing
Date
26 August 2024
Pages
56
ISBN
9786207844548