Mastering PyTorch

• Verfasst von: Jha, Ashish Ranjan [VerfasserIn]
• Titel: Mastering PyTorch
• Titelzusatz: create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond
• Verf.angabe: Ashish Ranjan Jha
• Ausgabe: Second edition.
• Verlagsort: Birmingham, UK
• Verlag: Packt Publishing Ltd.
• Jahr: 2024
• Umfang: 1 online resource (558 pages)
• Illustrationen: illustrations
• Gesamttitel/Reihe: Expert insight
• Fussnoten: Includes bibliographical references and index
• ISBN: 978-1-80107-430-8
• Datenträger: Online-Ressource
• Sprache: eng
• Bibliogr. Hinweis: Erscheint auch als : Druck-Ausgabe: Jha, Ashish Ranjan: Mastering PyTorch. - Second edition. - Birmingham : Packt Publishing Limited, 2024. - xxi, 534 Seiten
• RVK-Notation: ST 250
• RVK-Notation: ST 301
• Sach-SW: Réseaux neuronaux (Informatique)
• Sach-SW: Python (Langage de programmation)
• Sach-SW: Intelligence artificielle
• Sach-SW: artificial intelligence
• K10plus-PPN: 1892758075
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4544424313
• Lokale URL Inst.: Zum Volltext

Abstract

PyTorch is making it easier than ever before for anyone to build deep learning applications. This PyTorch deep learning 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 learning 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 learning models in PyTorch but also learn 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 learning 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 learning tasks using PyTorch to build smart artificial intelligence models.