Google has many GDEs (Google Developers Experts) around the world, all of whom are recognized experts by Google. GDEs are committed to spreading and promoting new technologies in various forms and helping developers solve problems encountered during the development process.
Each GDE has made special contributions to their respective fields.
The author of “A Simple and Direct Guide to TensorFlow”, Li Xihan, is actively engaged in promoting TensorFlow. This concise TensorFlow introductory guide is based on TensorFlow’s Eager Execution (dynamic graph) mode, aiming to help developers with a certain foundation in machine learning and Python quickly get started with TensorFlow.
Tutorial Directory
1. Introduction
2. TensorFlow Installation
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Easy Installation
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Formal Installation
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Your First Program
3. TensorFlow Basics
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TensorFlow 1+1
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Basic Example: Linear Regression
4. TensorFlow Models
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Model and Layer
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Basic Example: Multilayer Perceptron (MLP)
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Convolutional Neural Network (CNN)
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Recurrent Neural Network (RNN)
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Deep Reinforcement Learning (DRL)
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Custom Layers *
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Graph Execution Mode *
5. TensorFlow Extensions
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Checkpoint: Saving and Restoring Variables
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TensorBoard: Visualization of Training Process
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Using and Allocating GPU
6. Appendix: Static TensorFlow
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TensorFlow 1+1
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Basic Example: Linear Regression
Download Complete Content PDF:
https://www.tensorflowers.cn/t/6230
Q&A
If you find any parts difficult to understand while reading, please check if you have a clear understanding of the “Prerequisite Knowledge” section for each chapter.
If you have any questions about this tutorial, please ask in the TensorFlow Chinese Community (tensorflowers.cn) in this section.
Note: This section link
https://www.tensorflowers.cn/b/48
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