【学习】Tensorflow机器学习宝典的代码

• Ch 1: Getting Started with TensorFlow

• Ch 2: The TensorFlow Way

• Ch 3: Linear Regression

• Ch 4: Support Vector Machines

• Ch 5: Nearest Neighbor Methods

• Ch 6: Neural Networks

• Ch 7: Natural Language Processing

• Ch 8: Convolutional Neural Networks

• Ch 9: Recurrent Neural Networks

• Ch 10: Taking TensorFlow to Production

• Ch 11: More with TensorFlow

Ch 1: Getting Started with TensorFlow

This chapter intends to introduce the main objects and concepts in TensorFlow.  We also introduce how to access the data for the rest of the book and provide additional resources for learning about TensorFlow.

1. General Outline of TF Algorithms

• Here we introduce TensorFlow and the general outline of how most TensorFlow algorithms work.

• How to create and initialize tensors in TensorFlow.  We also depict how these operations appear in Tensorboard.

• How to create and use variables and placeholders in TensorFlow.  We also depict how these operations appear in Tensorboard.

• Understanding how TensorFlow can work with matrices is crucial to understanding how the algorithms work.

• How to use various mathematical operations in TensorFlow.

• Activation functions are unique functions that TensorFlow has built in for your use in algorithms.

• Here we show how to access all the various required data sources in the book.  There are also links describing the data sources and where they come from.

• Mostly official resources and papers.  The papers are TensorFlow papers or Deep Learning resources.

链接：

https://github.com/nfmcclure/tensorflow_cookbook

原文链接：

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