Handbook of Deep Learning Models: Volume One: Fundamentals [Hardcover]

This volume covers a comprehensive range of fundamental concepts in deep learning and artificial neural networks, making it suitable for beginners looking to learn the basics.

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This volume covers a comprehensive range of fundamental concepts in deep learning and artificial neural networks, making it suitable for beginners looking to learn the basics.

Using Keras, a popular neural network API in Python, this book offers practical examples that reinforce the theoretical concepts discussed. Real-world case studies add relevance by showing how deep learning is applied across various domains. The book covers topics such as layers, activation functions, optimization algorithms, backpropagation, convolutional neural networks (CNNs), data augmentation, and transfer learning  providing a solid foundation for building effective neural network models.

This book is a valuable resource for anyone interested in deep learning and artificial neural networks, offering both theoretical insights and practical implementation experience.

Part I  Fundamentals of Deep Learning 1. Introduction to Deep Learning 2. Machine Learning Fundamentals 3. Neural Networks Fundamentals Part II Deep Learning Models with Use Case Studies 4. Convolutional Neural Networks 5. Recurrent Neural Networks 6. Generative Adversarial Networks 7. Radial Basis Function Networks 8. Self Organizing Maps

Anuj Bhardwaj is a distinguished author, educator, and entrepreneur, currently serving as the director, IQAC, and professor of computer science and engineering at Chandigarh University, and Founder of Data Matrix Experts Pvt. Ltd. With over 17 years of academic and research experience, he holds a PhD in computer science and a masters from BIT Mesra. Dr. Bhardwaj has authored six books with leading publishlƒP