This book is a foundational text in the field of machine learning. The book provides a comprehensive introduction to the principles, algorithms, and methodologies that underpin machine learning, making it suitable for both beginners and experienced practitioners. The book systematically explains key topics such as supervised learning, unsupervised learning, reinforcement learning, and decision tree algorithms, while also delving into concepts like neural networks, Bayesian learning, and genetic algorithms. The text is notable for its clear explanations and practical approach, offering mathematical rigor alongside real world examples to help readers understand how machine learning can be applied to solve complex problems. This Indian adaptation introduces four new chapters, deep learning, unsupervised learning, natural language processing, and support vector machines & Kernel methods.