3 Review(s)

Deep Learning Essentials: Theory and Practice provides a complete introduction to the concepts, techniques, and real-world applications of deep learning. Covering fundamental topics such as neural networks, backpropagation, convolutional networks, recurrent networks, and transfer learning, this book bridges theory with hands-on practice. Through detailed explanations, coding examples, and case studies, readers will develop a strong understanding of how to build, train, and deploy deep learning models. Ideal for students, researchers, and tech professionals, this book equips readers with the knowledge and skills to solve complex problems using state-of-the-art AI techniques