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Tensorflow in Action

🌀 《TensorFlow实战》 黄文坚 | 唐源 - 源代码讲解

  • 1 TensorFlow基础

    • 1.1 TensorFlow概要

    • 1.2 TensorFlow编程模型简介

  • 2 TensorFlow和其他深度学习框架对比

    • 2.1 主流深度学习框架对比

    • 2.2 各深度学习框架简介

  • 3 TensorFlow第一步

    • 3.1 TensorFlow的编译与安装

    • 3.2 TensorFlow实现Softmax Regression识别手写数字

  • 4 TensorFlow实现自编码机和多层感知机

    • 4.1 自编码机简介

    • 4.2 TensorFlow实现自编码器

    • 4.3 多层感知机简介

    • 4.4 TensorFlow实现多层感知器

  • 5 TensorFlow实现卷积神经网络

    • 5.1 卷积神经网络简介

    • 5.2 TensorFlow实现简单的卷积网络

    • 5.3 TensorFlow实现进阶的卷积网络

  • 6 TensorFlow实现经典卷积神经网络

    • 6.1 TensorFlow实现AlexNet

    • 6.2 TensorFlow实现VGGNet

    • 6.3 TensorFlow实现GoogleInceptionNet

    • 6.4 TensorFlowResNet

    • 6.5 卷积神经网络发展趋势

  • 7 TensorFlow实现循环神经网络及Word2Vec

    • 7.1 TensorFlow实现Word2Vec

    • 7.2 TensorFlow实现基于LSTM的语言模型

    • 7.3 TensorFlow实现BidirectionalLSTMClassifier

  • 8 TensorFlow实现深度强化学习

    • 8.1 深度强化学习简介

    • 8.2 TensorFlow实现策略网络

    • 8.3 TensorFlow实现估值网络

  • 9 TensorBoard、多GPU并行及分布式并行

    • 9.1 TensorBoard

    • 9.2 多GPU并行

    • 9.3 分布式并行

  • 10 TF.learn从入门到精通

    • 10.1 分布式Estimator

    • 10.2 深度学习Estimator

    • 10.3 机器学习Estimator

    • 10.4 DataFrame

    • 10.5 监督其Monitors

  • 11 TF.Contrib的其他组件

    • 11.1 统计分布

    • 11.2 Layer模块

    • 11.3 性能分析器tfprof

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