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CS231n-Note-Translation_CN

入门课程选择

开始学习深度学习,迎接人工智能浪潮的到来,希望为时不晚。

入门课程查询了一下,比较推荐的有三门课程

    1. Udacity Machine Learning Nanodegree
    1. Stanford CS231n class, 李飞飞的课程
    1. Andrew Ng的机器学习 (Machine Learning - Stanford University | Coursera)

当然远远不止以上这些,综合考虑了一下,Udacity的课程需要付费,虽然大多数资源都是免费的,但不是特别考虑。 吴恩达的课程,大家都推荐,但是想要专门了解一下图像识别相关的知识,所以还是选择了李飞飞的CS231n。

具体这里有讲解 人工智能自学心得 - 知乎专栏

知乎上面的一个好问题 普通程序员如何向人工智能靠拢? - 知乎

CS231n相关资源

课程官网:CS231n: Convolutional Neural Networks for Visual Recognition

Github:https://github.com/cs231n/cs231n.github.io | http://cs231n.github.io/

教学安排及大纲:Schedule and Syllabus 课程视频:Youtube上查看Andrej Karpathy创建的播放列表,或者网易云课堂

课程pdf及视频下载:百度网盘下载,密码是4efx

CS231课程笔记翻译 https://zhuanlan.zhihu.com/intelligentunit

这里是一个总结:http://www.jianshu.com/p/182baeb82c71, 主要参考的这里

搬运过来,自己学习,内容属于原作者

学习一点,搬运一点

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