Deep Learning Networks

[Khushwant-Singh1]

This book, written by AI and machine learning experts, is unique. Unlike current
books on this subject that either cover the theory and mathematical underpinnings
of deep learning, or focus exclusively on programming-centric concepts, tools and
languages, this book addresses, and bridges both aspects. It seamlessly connects
theoretical methods with pertinent technologies and toolsets in a manner that makes
the material suitable for students, educators, and practitioners.
Its proposition lies in its multifaceted treatment of the subject. It conveys complex deep-learning concepts in simple terms, making the material understandable
to a wide audience. In addition, it elucidates the intricate landscape of the different
technologies and toolsets currently available, thereby offering readers the much
needed clarity needed to make informed decisions for their respective applications
and problem domains.
By bridging theory and practice, this book empowers readers to not only grasp
fundamental concepts but also to confidently navigate the practical applications of
Deep Learning. Ultimately, this book will serve as a comprehensive guide to Deep
Learning enthusiasts, practitioners, educators, and researchers alike. Its focus on
holistic understanding and actionable insights makes it an invaluable “must-read,”
and an essential resource for anyone interested in delving into the exciting realm of
Deep Learning.