Beginner-Friendly Approach: A comprehensive guide crafted for those with zero coding or advanced math background, making machine learning accessible to all.

Practical, Hands-On Learning: Features hands-on exercises and real-world applications to ensure concepts stick and prepare you for practical use.

Essential Python & Math Basics: Teaches the fundamental Python and math essentials from scratch, so you don't need any prior knowledge.

Multi-Format Support: Includes QR-based video lessons and online MCQs for self-testing, offering a modern, supported learning experience.

Broad Audience Appeal: Tailored for a wide audience, including college students, faculty, software professionals, and anyone curious about the field.

This book provides a hands-on approach with live examples of machine learning written for engineers, college students in their second or third year as well as for professionals, and faculty members who want to learn this exciting field on their own. The book focuses on explaining concepts of machine learning, which are important in applications. Some theoretical aspects are covered, to give enough intuition on how machine learning works, but without too much detail which can get a first-time student bogged down.
Key Features:
A comprehensive approach to Machine Learning makes the book accessible to self-learning faculty members, professionals, and college students.
Numerous practical tips and Appendices on Basic Maths and Python Programming.
Step-by-step hands-on exercises to help illustrate the concepts presented.
Multiple choice questions with scoring (available online) for a quick test of the understanding of concepts.
Set of complementary videos after each chapter with a QR code.