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PyTorch Deep Learning Hands-On
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PyTorchDeepLearningHands-Onisabookforengineerswhowantafast-pacedguidetodoingdeeplearningworkwithPytorch.Itisnotanacademictextbookanddoesnottrytoteachdeeplearningprinciples.ThebookwillhelpyoumostifyouwanttogetyourhandsdirtyandputPyTorchtoworkquickly.PyTorchDeepLearningHands-OnshowshowtoimplementthemajordeeplearningarchitecturesinPyTorch.Itcoversneuralnetworks,computervision,CNNs,naturallanguageprocessing(RNN),GANs,andreinforcementlearning.YouwillalsobuilddeeplearningworkflowswiththePyTorchframework,migratemodelsbuiltinPythontohighlyefficientTorchScript,anddeploytoproductionusingthemostsophisticatedavailabletools.Eachchapterfocusesonadifferentareaofdeeplearning.Chaptersstartwitharefresheronhowthemodelworks,beforesharingthecodeyouneedtoimplementtheminPyTorch.ThisbookisidealifyouwanttorapidlyaddPyTorchtoyourdeeplearningtoolset.
目錄(64章)
倒序
- 封面
- 版權頁
- Why subscribe?
- Packt.com
- Contributors
- About the authors
- About the reviewers
- Preface
- Who this book is for
- What this book covers
- To get the most out of this book
- Get in touch
- Chapter 1. Deep Learning Walkthrough and PyTorch Introduction
- Understanding PyTorch's history
- What is PyTorch?
- Using computational graphs
- Exploring deep learning
- Getting started with the code
- Chapter 2. A Simple Neural Network
- Introduction to the neural network
- The problem
- Dataset
- Novice model
- The PyTorch way
- Summary
- References
- Chapter 3. Deep Learning Workflow
- Ideation and planning
- Design and experimentation
- Model implementation
- Training and validation
- Summary
- References
- Chapter 4. Computer Vision
- Introduction to CNNs
- Computer vision with PyTorch
- Chapter 5. Sequential Data Processing
- Introduction to recurrent neural networks
- The problem
- Approaches
- Summary
- References
- Chapter 6. Generative Networks
- Defining the approaches
- Autoregressive models
- GANs
- Summary
- References
- Chapter 7. Reinforcement Learning
- The problem
- Episodic versus continuous tasks
- Cumulative discounted rewards
- Markov decision processes
- The solution
- Summary
- References
- Chapter 8. PyTorch to Production
- Serving with Flask
- ONNX
- Efficiency with TorchScript
- Exploring RedisAI
- Summary
- References
- Index 更新時間：2021-06-11 13:28:31
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