Applied Machine Learning|2nd Edition

Book Details:

• Publisher: McGraw-Hill Education

• Author: M. Gopal

• Language: English

• Binding: Paperback

• Edition: Second Edition

• ISBN: 9789354601590

• Number of Pages: 552

• Dimensions: 9.3 x 7.3 x 0.9 inches

• Release Date: 17-12-2021

About The Book:

"Applied Machine Learning" (Second Edition) by M. Gopal is designed to provide readers with a clear, step-by-step guide to mastering machine learning techniques and applying them to real-world problems. The book offers a comprehensive approach to the concepts of machine learning, from the theoretical foundations to practical applications, making it accessible even to those with limited mathematical expertise.

This edition includes expanded content on a variety of techniques such as log loss (cross entropy) for classification, handling imbalanced data, Ridge and LASSO regression, and multiclass logistic regression. In addition to the core content, the book introduces a new chapter titled "Understanding Machine Learning by Application," which provides hands-on experience through case studies from real-life problems. The inclusion of practical exercises and datasets further enhances the learning experience, ensuring readers are equipped to apply machine learning methods effectively.

Key Features:

• Comprehensive Coverage: Covers a broad array of machine learning methods, including modern techniques like Ridge and LASSO regression, and multiclass logistic regression.

• Non-Rigorous Mathematical Approach: Concepts are explained in a simple, lucid manner with minimal mathematical complexity, making it accessible to a wider audience.

• Hands-On Learning: The new chapter on "Understanding Machine Learning by Application" includes case studies and exercise experiments that help readers gain practical experience.

• Updated Content: Includes new sections on imbalanced data problems and solutions, softmax function, and cross entropy metrics for classification.

• Practical Datasets: Datasets in Excel files are available online for the case studies and exercises, enabling readers to practice the techniques learned in the book.

Ideal for:

• Machine Learning Enthusiasts: Whether you're new to the field or looking to expand your knowledge, this book serves as an excellent resource for understanding machine learning concepts and techniques.

• Students and Professionals: Those studying or working in the fields of data science, artificial intelligence, or applied mathematics will find this book useful.

• Hands-On Learners: The practical case studies and exercises make this a great resource for those looking to gain hands-on experience in machine learning.

Conclusion:

"Applied Machine Learning" (Second Edition) by M. Gopal is an essential resource for anyone looking to understand and apply machine learning techniques. With clear explanations, hands-on examples, and up-to-date content, this book is an invaluable guide for solving real-world problems using machine learning.