Deep Learning with Python - Learn Best Practices of Deep Learning Models with PyTorch (2nd Edition) - Ketkar, Nikhil; Moolayil, Jojo (Apress, an imprint of Springer Nature, 2021)
Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by Facebook's Artificial Intelligence Research Group. You'll also gain an understanding of Graphical Processing Unit (GPU) based computation, which is essential for training deep learning models. All the key architectures in deep learning are covered, including feedforward networks, convolution neural networks, recurrent neural networks, long short-term memory networks, autoencoders and generative adversarial networks. Backed by a number of tricks of the trade for training and optimizing deep learning models, this edition of this book explains the best practices in taking these models to production with PyTorch.