This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time applications. This book intro

"This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statist

Rigorous treatment of the theory of deep learning from first principles, with applications to beautiful problems in the natural sciences.

Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the P

All engineers and applied scientists will need to harness the power of machine learning to solve the highly complex and data intensive problems now emerging. Th