#!/usr/bin/env python
# coding: utf-8

# # “用于视觉识别的卷积神经网络”笔记
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# ## 简介
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# **作者：子实**
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# CS231n Convolutional Neural Networks for Visual Recognition 作业，使用 `jupyter notebook` 完成。
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# `Github` 加载 `.ipynb` 的速度较慢，建议在 [Nbviewer](http://nbviewer.jupyter.org/github/zlotus/cs231n/blob/master/ReadMe.ipynb?flush_cache=true) 中查看。
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# ----
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# ## 目录
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# 来自斯坦福网络课程“CS231n Convolutional Neural Networks for Visual Recognition”的作业：
# * 原文笔记：[CS231n: Convolutional Neural Networks for Visual Recognition](http://cs231n.github.io/) 
# * 授课视频：[CS231n Winter 2016](https://www.youtube.com/playlist?list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC) 
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# 
# ### 1. [Assignment 1](http://cs231n.github.io/assignments2016/assignment1/)
#   * [k-Nearest Neighbor classifier](assignment1/knn.ipynb)
#   * [Training a Support Vector Machine](assignment1/svm.ipynb)
#   * [Implement a Softmax classifier](assignment1/softmax.ipynb)
#   * [Two-Layer Neural Network](assignment1/two_layer_net.ipynb)
#   * [Higher Level Representations: Image Features](assignment1/features.ipynb)
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# ### 2. [Assignment 2](http://cs231n.github.io/assignments2016/assignment2/)
#   * [Fully-connected Neural Network](assignment2/FullyConnectedNets.ipynb)
#   * [Batch Normalization](assignment2/BatchNormalization.ipynb)
#   * [Dropout](assignment2/Dropout.ipynb)
#   * [ConvNet on CIFAR-10](assignment2/ConvolutionalNetworks.ipynb)
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# ### 3. [Assignment 3](http://cs231n.github.io/assignments2016/assignment3/)
#   * [Image Captioning with Vanilla RNNs](assignment3/RNN_Captioning.ipynb)
#   * [Image Captioning with LSTMs](assignment3/LSTM_Captioning.ipynb)
#   * [Image Gradients: Saliency maps and Fooling Images](assignment3/ImageGradients.ipynb)
#   * [Image Generation: Classes, Inversion, DeepDream](assignment3/ImageGeneration.ipynb)
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