DEEP LEARNING WITH PYTHON IBD

Sinopse

Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated editionáwill 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 FacebookâÇÖs Artificial Intelligence Research Group.YouâÇÖll start with a perspective on how and why deep learning with PyTorch has emerged as an path-breaking framework with a set of tools and techniques to solve real-world problems. Next, the book will ground you with the mathematical fundamentals of linear algebra, vector calculus, probability and optimization. Having established this foundation, youâÇÖll move on to key components and functionality of PyTorch including layers, loss functions and optimization algorithms.áYouâÇÖll 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 Deep Learning with Python explains the best practices in taking these models to production with PyTorch.What YouâÇÖll LearnReview machine learning fundamentals such as overfitting, underfitting, and regularization.Understand deep learning fundamentals such as feed-forward networks, convolution neural networks, recurrent neural networks, automaticádifferentiation, and stochasticágradient descent.Apply in-depth linear algebra with PyTorchExplore PyTorch fundamentals and its building blocksWork with tuning and optimizing modelsáWho This Book Is ForBeginnersáwith a working knowledge of Python who want to understand Deep Learning in a practical, hands-on manner.á á á