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The Deep Learning with PyTorch Workshop
Wanttogettogripswithoneofthemostpopularmachinelearninglibrariesfordeeplearning?TheDeepLearningwithPyTorchWorkshopwillhelpyoudojustthat,jumpstartingyourknowledgeofusingPyTorchfordeeplearningevenifyou’restartingfromscratch.It'snosurprisethatdeeplearning'spopularityhasrisensteeplyinthepastfewyears,thankstointelligentapplicationssuchasself-drivingvehicles,chatbots,andvoice-activatedassistantsthataremakingourliveseasier.Thisbookwilltakeyouinsidetheworldofdeeplearning,whereyou'llusePyTorchtounderstandthecomplexityofneuralnetworkarchitectures.TheDeepLearningwithPyTorchWorkshopstartswithanintroductiontodeeplearninganditsapplications.You'llexplorethesyntaxofPyTorchandlearnhowtodefineanetworkarchitectureandtrainamodel.Next,you'lllearnaboutthreemainneuralnetworkarchitectures-convolutional,artificial,andrecurrent-andevensolvereal-worlddataproblemsusingthesenetworks.Laterchapterswillshowyouhowtocreateastyletransfermodeltodevelopanewimagefromtwoimages,beforefinallytakingyouthroughhowRNNsstorememorytosolvekeydataissues.Bytheendofthisbook,you'llhavemasteredtheessentialconcepts,tools,andlibrariesofPyTorchtodevelopyourowndeepneuralnetworksandintelligentapps.
目錄(47章)
倒序
- 封面
- 版權信息
- Experience the Workshop Online
- Preface
- 1. Introduction to Deep Learning and PyTorch
- Introduction
- Why Deep Learning?
- Introduction to PyTorch
- Summary
- 2. Building Blocks of Neural Networks
- Introduction
- Introduction to Neural Networks
- Data Preparation
- Building a Deep Neural Network
- Summary
- 3. A Classification Problem Using DNN
- Introduction
- Problem Definition
- Dealing with an Underfitted or Overfitted Model
- Deploying Your Model
- Summary
- 4. Convolutional Neural Networks
- Introduction
- Building a CNN
- Data Augmentation
- Batch Normalization
- Summary
- 5. Style Transfer
- Introduction
- Style Transfer
- Implementation of Style Transfer Using the VGG-19 Network Architecture
- Summary
- 6. Analyzing the Sequence of Data with RNNs
- Introduction
- Recurrent Neural Networks
- Long Short-Term Memory Networks
- LSTM Networks in PyTorch
- Natural Language Processing
- Sentiment Analysis in PyTorch
- Summary
- Appendix
- 1. Introduction to Deep Learning and PyTorch
- 2. Building Blocks of Neural Networks
- 3. A Classification Problem Using DNNs
- 4. Convolutional Neural Networks
- 5. Style Transfer
- 6. Analyzing the Sequence of Data with RNNs 更新時間：2021-06-18 18:22:35
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