目录 Preface Chapter 1: Getting Started with Mobile TensorFIow Setting up TensorFIow Setting up TensorFIow on MacOS Setting up TensorFIow on GPU-powered Ubuntu Setting up Xcode Setting up Android Studio TensorFIow Mobile vs TensorFIow Lite Running sample TensorFIow iOS apps Running sample TensorFIow Android apps Summary Chapter 2: Classifying Images with Transfer Learning Transfer learning - what and why Retraining using the Inception v3 model Retraining using MobileNet models Using the retrained models in the sample iOS app Using the retrained models in the sample Android app Adding TensorFIow to your own iOS app Adding TensorFIow to your Objective-C iOS app Adding TensorFIow to your Swift iOS app Adding TensorFIow to your own Android app Summary Chapter 3: Detecting Objects and Their Locations Object detection-a quick overview Setting up the TensorFIow Object Detection API Quick installation and example Using pre-trained models Retraining SSD-MobileNet and Faster RCNN models Using object detection models in iOS Building TensorFIow iOS libraries manually Using TensorFIow iOS libraries in an app Adding an object detection feature to an lOS app Using YOLO2-another object-detection model Summary Chapter 4: Transforming Pictures with Amazing Art Styles Neural Style Transfer - a quick overview Training fast neural-style transfer models Using fast neural-style transfer models in lOS Adding and testing with fast neural transfer models Looking back at the lOS code using fast neural transfer models Using fast neural-style transfer models in Android Using the TensorFIow Magenta multi-style model in lOS Using the TensorFIow Magenta multi-style model in Android Summary Chapter 5: Understanding Simple Speech Commands Speech recognition - a quick overview Training a simple commands recognition model Using a simple speech recognition model in Android Building a new app using the model Showing model-powered recognition results Using a simple speech recognition model in lOS with Objective-C Building a new app using the model Fixing model-loading errors with tf_op_files.txt Using a simple speech recognition model in lOS with Swift Summary Chapter 6: Describing Images in Natural Language Image captioning - how it works Training and freezing an image captioning model Training and testing caption generation Freezing the image captioning model Transforming and optimizing the image captioning model Fixing errors with transformed models Optimizing the transformed model Using the image captioning model in lOS Using the image captioning model in Android Summary Chapter 7: Recognizing Drawing with CNN and LSTM Drawing classification - how it works Training, predicting, and preparing the drawing classification model Training the drawing classification model Predicting with the drawing classification model Preparing the drawing classification model Using the drawing classification model in lOS Building custom TensorFIow library for lOS Developing an lOS app to use the model Using the drawing classification model in Android Building custom TensorFIow library for Android Developing an Android app to use the model Summary Chapter 8: Predicting Stock Price with RNN RNN and stock price prediction - what and how Using the TensorFIow RNN API for stock price prediction Training an RNN model in TensorFIow Testing the TensorFIow RNN model Using the Keras RNN LSTM API for stock price prediction Training an RNN model in Keras Testing the Keras RNN model Running the TensorFIow and Keras models on iOS Running the TensorFIow and Keras models on Android Summary Chapter 9: Generating and Enhancing Images with GAN GAN - what and why Building and training GAN models with TensorFIow Basic GAN model of generating handwritten digits Advanced GAN model of enhancing image resolution Using the GAN models in iOS Using the basic GAN model Using the advanced GAN model Using the GAN models in Android Using the basic GAN model Using the advanced GAN model Summary Chapter 10: Building an AlphaZero-like Mobile Game App AlphaZero - how does it work? Training and testing an AlphaZero-like model for Connect 4 Training the model Testing the model Looking into the model-building code Freezing the model Using the model in iOS to play Connect 4 Using the model in Android to play Connect 4 Summary Chapter 11: Using TensorFIow Lite and Core ML on Mobile TensorFIow Lite - an overview Using TensorFIow Lite in iOS Running the example TensorFIow Lite iOS apps Using a prebuilt TensorFIow Lite model in iOS Using a retrained TensorFIow model for TensorFIow Lite in iOS Using a custom TensorFIow Lite model in iOS Using TensorFIow Lite in Android Core ML for iOS - an overview Using Core ML with Scikit-Learn machine learning Building and converting the Scikit Learn models Using the converted Core ML models in iOS Using Core ML with Keras and TensorFIow Summary Chapter 12: Developing TensorFIow Apps on Raspberry Pi Setting up Raspberry Pi and making it move Setting up Raspberry Pi Making Raspberry Pi move Setting up TensorFIow on Raspberry Pi Image recognition and text to speech Audio recognition and robot movement Reinforcement learning on Raspberry Pi Understanding the CartPole simulated environment Starting with basic intuitive policy Using neural networks to build a better policy Summary Final words Other Books You May Enjoy Index
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