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Supplementary introduction and explanation
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Jzow authored Dec 26, 2023
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# MSVC Windows builds of rustc generate these, which store debugging information
*.pdb

.idea
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# Rust 深度学习教程

![](https://img.shields.io/badge/License-MIT%20OR%20Apache--2.0-Green)
![](https://img.shields.io/badge/Rust-1.73-red?logo=rust)
![](https://img.shields.io/badge/pytorch-2.1-blue?logo=pytorch)
![](https://img.shields.io/badge/tensorflow-2.0-8A2BE2?logo=tensorflow)

## 简介

本教程是基于《深度学习》和《动手学习深度学习》两本书籍的灵感,结合了 TensorFlow 和 PyTorch 框架,用 Rust 语言编写而成。
它的目标是为对 Rust 语言感兴趣并且对深度学习有兴趣的朋友们编写的。本教程以文档和代码相结合的方式进行讲解。如果你从未接
触过 Rust 语言开发,我们建议你先学习 Rust 语言的基础知识和掌握基本语法。对于那些从未接触过人工智能相关知识的朋友,
我们建议你先阅读《深度学习》和《动手学习深度学习》这两本书籍,以便更好地掌握一些基础数学知识。


## 许可证

根据以下任一许可

- Apache License, Version 2.0, ([LICENSE-APACHE](LICENSE-APACHE)<https://opensource.wansenai.com/apache2.0>)
- MIT license ([LICENSE-MIT](LICENSE-MIT)<https://opensource.wansenai.com/mit>)

根据您的选择。

### 贡献

除非您另有明确声明,否则根据Apache-2.0许可证的定义,您有意提交以包含在作品中的任何贡献都应具有上述双重许可,
无需任何额外条款或条件。
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# rust-deeplearnging-tutorials
:book: Learn deep learning in Rust language
# Rust Deep Learning Tutorials

![](https://img.shields.io/badge/License-MIT%20OR%20Apache--2.0-Green)
![](https://img.shields.io/badge/Rust-1.73-red?logo=rust)
![](https://img.shields.io/badge/pytorch-2.1-blue?logo=pytorch)
![](https://img.shields.io/badge/tensorflow-2.0-8A2BE2?logo=tensorflow)

## Introduction

This tutorial is inspired by two books, Deep Learning and Hands on Learning, and is written in Rust language, combining
TensorFlow and PyTorch frameworks. Its goal is to be written for friends who are interested in the Rust language and are
interested in deep learning. This tutorial is explained through a combination of documentation and code. If you have
never been exposed to the development of the Rust language, we suggest that you first learn the basic knowledge of the
Rust language and master the basic syntax. For friends who have never been exposed to artificial intelligence related
knowledge, we suggest that you first read two books, "Deep Learning" and "Hands on Learning Deep Learning", in order to
better grasp some basic mathematical knowledge.


## License

Licensed under either of

- Apache License, Version 2.0, ([LICENSE-APACHE](LICENSE-APACHE) or <https://opensource.wansenai.com/apache2.0>)
- MIT license ([LICENSE-MIT](LICENSE-MIT) or <https://opensource.wansenai.com/mit>)

at your option.

### Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the
work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any
additional terms or conditions.

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