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Hands-On Deep Learning for Images with TensorFlow
TensorFlowisGoogle’spopularofferingformachinelearninganddeeplearning,quicklybecomingafavoritetoolforperformingfast,efficient,andaccuratedeeplearningtasks.Hands-OnDeepLearningforImageswithTensorFlowshowsyouthepracticalimplementationsofreal-worldprojects,teachingyouhowtoleverageTensorFlow’scapabilitiestoperformefficientimageprocessingusingthepowerofdeeplearning.Withthehelpofthisbook,youwillgettogripswiththedifferentparadigmsofperformingdeeplearningsuchasdeepneuralnetsandconvolutionalneuralnetworks,followedbyunderstandinghowtheycanbeimplementedusingTensorFlow.Bytheendofthisbook,youwillhavemasteredalltheconceptsofdeeplearningandtheirimplementationwithTensorFlowandKeras.
目錄(53章)
倒序
- 封面
- Title Page
- Copyright and Credits
- Hands-On Deep Learning for Images with TensorFlow
- Packt Upsell
- Why subscribe?
- PacktPub.com
- Contributors
- About the author
- Packt is searching for authors like you
- Preface
- Who this book is for
- What this book covers
- To get the most out of this book
- Download the example code files
- Conventions used
- Get in touch
- Reviews
- Machine Learning Toolkit
- Installing Docker
- The machine learning Docker file
- Sharing data
- Machine learning REST service
- Summary
- Image Data
- MNIST digits
- Tensors – multidimensional arrays
- Turning images into tensors
- Turning categories into tensors
- Summary
- Classical Neural Network
- Comparison between classical dense neural networks
- Activation and nonlinearity
- Softmax
- Training and testing data
- Dropout and Flatten
- Solvers
- Hyperparameters
- Grid searches
- Summary
- A Convolutional Neural Network
- Convolutions
- Pooling
- Building a convolutional neural network
- Deep neural network
- Summary
- An Image Classification Server
- REST API definition
- Trained models in Docker containers
- Making predictions
- Summary
- Other Books You May Enjoy
- Leave a review - let other readers know what you think 更新時間：2021-07-16 18:17:31
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