A significant portion of the book is dedicated to how networks learn. Kumar covers the primary categories of machine learning:
This textbook comes from the expertise of , a long-time academic in the field. During the book's development, Dr. Kumar served as a Professor and Head of the Department of Physics and Computer Science at the Dayalbagh Educational Institute (Deemed University) in Agra, India, where he also coordinated the Neural Networks and Multimedia Labs. His deep involvement in teaching neural networks at both undergraduate and graduate levels directly informed the book's classroom-focused design and accessibility. Neural Networks A Classroom Approach By Satish Kumar.pdf
A: The book is primarily published for the Indian subcontinent (by Pearson or other local presses). International distribution is limited. Contact Pearson India or check Amazon.in. A significant portion of the book is dedicated
Several features distinguish this textbook: Kumar served as a Professor and Head of
A PDF alone can be dry. Search YouTube for “Backpropagation example Satish Kumar” or “Neural networks classroom approach” to find instructors walking through the same examples.
Neural Networks: A Classroom Approach by Satish Kumar is a widely utilized engineering textbook providing an intuitive, geometric introduction to artificial neural networks, bridging biological concepts with computational intelligence. The second edition offers comprehensive coverage, including supervised learning, recurrent networks, and MATLAB-based simulations. For details on the second edition, visit McGraw Hill . Neural Networks- A Classroom Approach - McGraw Hill
Kumar's book, "Neural Networks: A Classroom Approach", offers a comprehensive and engaging introduction to neural networks. The author presents complex concepts in a clear and concise manner, making the book an ideal resource for students, researchers, and professionals seeking to understand the fundamentals of neural networks.
