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142533773
Mastering PyTorch: Create and deploy deep learning models from CNNs to multimodal models LLMs and beyond
87% of respondents would recommend this to a friend
Item #:
142533773
XAF 41544
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What Stands Out
Comprehensive Coverage
This book provides an in-depth exploration of deep learning techniques, from CNNs to LLMs, making it ideal for both beginners and advanced practitioners seeking to enhance their knowledge.
Hands-On Projects
Includes practical projects that guide readers through deploying models, empowering them to apply concepts in real-world scenarios, reinforcing learning through practical application.
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Authored by leading experts in the field, offering valuable insights and best practices, ensuring readers are equipped with the latest trends and knowledge in deep learning technologies.
Product Details
- Master advanced techniques and algorithms for machine learning with PyTorch using real-world examplesUpdated for PyTorch 2.x, including integration with Hugging Face, mobile deployment, diffusion models, and graph neural networksGet With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader FreeKey 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 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.What you will learnImplement 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 learning models using CaptumDesign ResNets, LSTMs, and graph neural networks (GNNs)Create language and vision transformer models using Hugging FaceWho this book is forThis deep learning with PyTorch book is for data scientists, machine learning engineers, machine learning researchers, and deep learning practitioners looking to implement advanced deep learning models using PyTorch. This book is ideal for those looking to switch from TensorFlow to PyTorch. Working knowledge of deep learning with Python is required.Table of ContentsOverview of Deep Learning 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 LearningModel Training OptimizationsOperationalizing PyTorch Models into ProductionPyTorch on Mobile DevicesRapid Prototyping with PyTorchPyTorch and AutoMLPyTorch and Explainable AIRecommendation Systems with TorchRecPyTorch and Hugging Face
| Publisher | Packt Publishing |
| Publication date | 31 May 2024 |
| Edition | 2. |
| Language | English |
| Print length | 558 pages |
| ISBN-10 | 1801074305 |
| ISBN-13 | 978-1801074308 |
| Dimensions | 19.05 x 3.18 x 23.5 cm |
Who Should Buy?
-
Aspiring Data Scientists
Provides foundational and advanced knowledge of deep learning techniques using PyTorch, perfect for beginners.
-
AI Researchers
Covers cutting-edge developments and multimodal models, making it a valuable resource for ongoing research.
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Software Engineers
Equips engineers with practical skills to implement and deploy deep learning solutions in real-world applications.
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Absolute Beginners
Prior experience with programming or machine learning concepts may be necessary to fully grasp the content.
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Features & Benefits
- Master advanced deep learning techniques using PyTorch.
- Updated for PyTorch 2.x with cutting-edge integrations.
- Build complex models from CNNs to multimodal applications.
- Discover expert strategies for optimizing training and deployment.
- Includes free eBook with purchase of the print or Kindle edition.
- Ideal for data scientists and machine learning practitioners.
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