Mastering PyTorch: Create and deploy deep leaing models from CNNs to multimodal models, LLMs, and beyond

by: Ashish Ranjan Jha (Author)

Publisher: Packt Publishing

Edition: 2nd ed.

Publication Date: 2024/5/31

Language: English

Print Length: 558 pages

ISBN-10: 1801074305

ISBN-13: 9781801074308

Book Description

Master advanced techniques and algorithms for machine leaing with PyTorch using real-world examplesUpdated for PyTorch 2.x, including integration with Hugging Face, mobile deployment, diffusion models, and graph neural networksPurchase of the print or Kindle book includes a free eBook in PDF formatKey FeaturesUnderstand how to use PyTorch to build advanced neural network modelsGet the best from PyTorch by working with Hugging Face, fastai, PyTorch Lightning, PyTorch Geometric, Flask, and DockerUnlock faster training with multiple GPUs and optimize model deployment using efficient inference frameworksBook DescriptionPyTorch is making it easier than ever before for anyone to build deep leaing applications. This PyTorch deep leaing book will help you uncover expert techniques to get the most out of your data and build complex neural network models.You’ll build convolutional neural networks for image classification and recurrent neural networks and transformers for sentiment analysis. As you advance, you’ll apply deep leaing across different domains, such as music, text, and image generation, using generative models, including diffusion models. You’ll not only build and train your own deep reinforcement leaing models in PyTorch but also lea to optimize model training using multiple CPUs, GPUs, and mixed-precision training. You’ll deploy PyTorch models to production, including mobile devices. Finally, you’ll discover the PyTorch ecosystem and its rich set of libraries. These libraries will add another set of tools to your deep leaing toolbelt, teaching you how to use fastai to prototype models and PyTorch Lightning to train models. You’ll discover libraries for AutoML and explainable AI (XAI), create recommendation systems, and build language and vision transformers with Hugging Face.By the end of this book, you’ll be able to perform complex deep leaing tasks using PyTorch to build smart artificial intelligence models.What you will leaImplement text, vision, and music generation models using PyTorchBuild a deep Q-network (DQN) model in PyTorchDeploy PyTorch models on mobile devices (Android and iOS)Become well versed in rapid prototyping using PyTorch with fastaiPerform neural architecture search effectively using AutoMLEasily interpret machine leaing models using CaptumDesign ResNets, LSTMs, and graph neural networks (GNNs)Create language and vision transformer models using Hugging FaceWho this book is forThis deep leaing with PyTorch book is for data scientists, machine leaing engineers, machine leaing researchers, and deep leaing practitioners looking to implement advanced deep leaing models using PyTorch. This book is ideal for those looking to switch from TensorFlow to PyTorch. Working knowledge of deep leaing with Python is required.Table of ContentsOverview of Deep Leaing using PyTorchDeep CNN architecturesCombining CNNs and LSTMsDeep Recurrent Model ArchitecturesAdvanced Hybrid ModelsGraph Neural NetworksMusic and Text Generation with PyTorchNeural Style TransferDeep Convolutional GANsImage Generation Using DiffusionDeep Reinforcement LeaingModel Training OptimizationsOperationalizing PyTorch Models into ProductionPyTorch on Mobile DevicesRapid Prototyping with PyTorchPyTorch and AutoMLPyTorch and Explainable AIRecommendation Systems with TorchRecPyTorch and Hugging Face

About the Author

Master advanced techniques and algorithms for machine leaing with PyTorch using real-world examplesUpdated for PyTorch 2.x, including integration with Hugging Face, mobile deployment, diffusion models, and graph neural networksPurchase of the print or Kindle book includes a free eBook in PDF formatKey FeaturesUnderstand how to use PyTorch to build advanced neural network modelsGet the best from PyTorch by working with Hugging Face, fastai, PyTorch Lightning, PyTorch Geometric, Flask, and DockerUnlock faster training with multiple GPUs and optimize model deployment using efficient inference frameworksBook DescriptionPyTorch is making it easier than ever before for anyone to build deep leaing applications. This PyTorch deep leaing book will help you uncover expert techniques to get the most out of your data and build complex neural network models.You’ll build convolutional neural networks for image classification and recurrent neural networks and transformers for sentiment analysis. As you advance, you’ll apply deep leaing across different domains, such as music, text, and image generation, using generative models, including diffusion models. You’ll not only build and train your own deep reinforcement leaing models in PyTorch but also lea to optimize model training using multiple CPUs, GPUs, and mixed-precision training. You’ll deploy PyTorch models to production, including mobile devices. Finally, you’ll discover the PyTorch ecosystem and its rich set of libraries. These libraries will add another set of tools to your deep leaing toolbelt, teaching you how to use fastai to prototype models and PyTorch Lightning to train models. You’ll discover libraries for AutoML and explainable AI (XAI), create recommendation systems, and build language and vision transformers with Hugging Face.By the end of this book, you’ll be able to perform complex deep leaing tasks using PyTorch to build smart artificial intelligence models.What you will leaImplement text, vision, and music generation models using PyTorchBuild a deep Q-network (DQN) model in PyTorchDeploy PyTorch models on mobile devices (Android and iOS)Become well versed in rapid prototyping using PyTorch with fastaiPerform neural architecture search effectively using AutoMLEasily interpret machine leaing models using CaptumDesign ResNets, LSTMs, and graph neural networks (GNNs)Create language and vision transformer models using Hugging FaceWho this book is forThis deep leaing with PyTorch book is for data scientists, machine leaing engineers, machine leaing researchers, and deep leaing practitioners looking to implement advanced deep leaing models using PyTorch. This book is ideal for those looking to switch from TensorFlow to PyTorch. Working knowledge of deep leaing with Python is required.Table of ContentsOverview of Deep Leaing using PyTorchDeep CNN architecturesCombining CNNs and LSTMsDeep Recurrent Model ArchitecturesAdvanced Hybrid ModelsGraph Neural NetworksMusic and Text Generation with PyTorchNeural Style TransferDeep Convolutional GANsImage Generation Using DiffusionDeep Reinforcement LeaingModel Training OptimizationsOperationalizing PyTorch Models into ProductionPyTorch on Mobile DevicesRapid Prototyping with PyTorchPyTorch and AutoMLPyTorch and Explainable AIRecommendation Systems with TorchRecPyTorch and Hugging Face