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Copyright © Microsoft Corporation. All rights reserved.
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

# AI基本原理简明教程的目录

## 写在前面,为什么要出这个系列的教程呢?

Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可


总的说来,我们现在有了很多非常厉害的深度学习框架,比如tensorflow,pytorch,paddlepaddle,caffe2等等等等。然而,我们用这些框架在搭建我们自己的深度学习模型的时候,到底做了一些什么样的操作呢?我们试图去阅读框架的源码来理解框架到底帮助我们做了些什么,但是……很难!很难!很难!因为深度学习是需要加速啦,分布式计算啦,所以框架做了很多很多的优化,也让像我们这样的小白难以理解这些框架的源码。所以,为了帮助大家更进一步的了解神经网络模型的具体内容,我们整理了这样一个系列的教程。

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Copyright © Microsoft Corporation. All rights reserved.适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

# 微软System团队
# 人工智能应用开发实践课程
Copyright © Microsoft Corporation. All rights reserved.适用于[License](./LICENSE.md)版权许可


受众人群:具有人工智能理论基础/编程经验的的学生、程序员
# 课程概述
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# 目录

Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

[知识点](#知识点)

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Copyright © Microsoft Corporation. All rights reserved.
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

---
title: 机器学习平台建设
机器学习平台建设
---

本文从机器学习平台的架构开始,再到具体的功能,然后从需求的角度带给读者思考,找到合适的机器学习平台建设之路。最后,推荐了微软开源开放的机器学习平台OpenPAI,是可私有部署的机器学习训练平台。
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4 changes: 4 additions & 0 deletions B-教学案例与实践/B11-量化交易案例/README.md
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Copyright © Microsoft Corporation. All rights reserved.
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可


# 量化交易

1. 案例介绍
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# 问答系统与知识库
Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

https://www.cnblogs.com/ms-uap/p/9554734.html
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# 图像识别应用案例-看图识熊
Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

- 微软-方案1
- [教案](./微软-方案1/README.md)
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# 看图识熊
Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

**主要知识点:**

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# 智能家居
Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

**主要知识点:**

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# 目录
Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

[知识点](#知识点)

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# 基本函数导数公式

Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

这篇文章呢更多的是一些可能要用到的数学公式的推导,是一种理论基础,感兴趣的同学可以仔细瞅瞅,想直接上手的同学也可以直接跳过这一篇~

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Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

看过很多博客、文章,东一榔头西一棒子的,总觉得没有一个系列的文章把问题从头到尾说清楚,找东西很困难。有的博客、文章的质量还不算很理想,似是而非,或者重点不明确,或者直接把别人的博客抄袭过来......种种不靠谱,让小白们学习起来很困难,增加了学习曲线的陡峭程度。当然也有很多博主非常非常负责任,文章质量很高,只是连续度不够,正看得过瘾的时候,没有后续章节了。

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Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

反向传播和梯度下降这两个词,第一眼看上去似懂非懂,不明觉厉。这两个概念是整个神经网络中的重要组成部分,是和误差函数/损失函数的概念分不开的。

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Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

在这一章,我们将简要介绍一下损失函数,因为在下一章的内容中要首次用到损失函数的概念。

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Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

# 学习要点

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Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

# 知识点

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Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

# 知识点

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Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

在这一章,我们将简要介绍一下激活函数,因为在下一章中将要使用激活函数构造神经网络。

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Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

# 定义神经网络结构

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# AI基本原理简明教程的目录
Copyright © Microsoft Corporation. All rights reserved.
适用于[License](./LICENSE.md)版权许可
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

## 写在前面,为什么要出这个系列的教程呢?

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Copyright © Microsoft Corporation. All rights reserved.
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

基于本地模型的手写数字识别应用开发案例
===
使用Visual Studio Tools for AI加速桌面智能应用开发
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Copyright © Microsoft Corporation. All rights reserved.
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

# 针对时序数据的AI构建实战 - 基于“黄金点”游戏

**主要知识点:**
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扩展手写数字识别应用
Copyright © Microsoft Corporation. All rights reserved.
适用于[License](https://github.com/Microsoft/ai-edu/blob/master/LICENSE.md)版权许可

扩展手写数字识别应用
===
识别并计算简单手写数学表达式
---
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- 推荐在贡献的大纲、课件内容中说明适用对象、课程难度、建议课时等信息。

- 贡献到[B:教学案例与实践](./B-教学案例与实践/README.md)的可以为案例、教程、代码。
- 可以从此模块选取相应的案例进行教学。
- 可以贡献原创的教学案例及学生作业案例。
- 可以是一个新的案例,新建一个文件夹,包含案例说明和参考的code。
- 可以是对已经存在的案例,贡献不同的解决方案。如在 [自构建-图像识别应用案例-手写算式计算器](./B-学习资源/B9-自构建-图像识别应用案例-手写算式计算器/README.md) 案例模块中,可以为手写算式计算器添加其他的实现方案。格式举例如下,N为顺序号:
*[自构建-图像识别应用案例-手写算式计算器](./B-学习资源/B9-自构建-图像识别应用案例-手写算式计算器/README.md)模块下添加新的文件夹,命名格式为:<pre><code>[author+solutionN+title]</code></pre> n为该案例模块下的顺序第n个解决方案
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各模块内容和适用人群概述如下:

<font size=3>[A:教学课程](./A-教学课程/README.md) </font>
- 内容:包含微软及多个高校开源分享的人工智能教学大纲,课件,案例
- 内容:包含微软及多个高校开源分享的人工智能教学大纲,课件。
- 适用人群:
- 有意开设高校人工智能课程的老师:
- 可以从这个模块参考多个高校开源分享的教学大纲和课件,用于人工智能教学。
- 可以分享原创的教学大纲和课件或从[B-教学案例与实践](./B-教学案例与实践/README.md)选取相应案例自由组合成适合的人工智能教学大纲和课件,用于人工智能教学。
- 希望系统化了解高校人工智能学习大纲的学习者。

<font size=3>[B:教学案例与实践](./B-教学案例与实践/README.md)</font>
- 内容:包含微软及共建者开源分享的人工智能案例资源,包含案例、源代码、文档、教学视频等。
- 适用人群:
- 有意开设人工智能课程的教师:
- 可以从此模块选取相应的案例进行教学。
- 可以贡献原创的教学案例及学生作业案例。
- 有意进行人工智能应用开发的学习者
- 可以从此模块选取相应的案例进行学习。
- 可以贡献原创的开发案例,也可以基于已有的案例提供不同的解决方案。


<font size=3>[C:开发工具与环境](./C-开发工具与环境/README.md) </font>
- 内容:人工智能学习中需要用到的开发工具与环境搭建教程。
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