搬运的最新的2017 spring cs231n 课后编程作业，对学习深度学习很有用

斯坦福大学的计算机视觉课程（课程代号：cs231n）笔记（pdf版）

斯坦福李飞飞-深度学习计算机视觉课程笔记的中文版，知乎上杜克版本的PDF版本，整理为全一册pdf，带书签

做cs231n时候的作业上使用到的机器学习分类数据集。 国内下载速度巨慢，而且还需要使用linux系统才能运行那个脚本，因此直接贴在CSDN上。 The CIFAR-10 and CIFAR-100 are labeled subsets of the 80 million tiny images dataset. They were collected by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton. The CIFAR-10 dataset The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images. The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may contain more images from one class than another. Between them, the training batches contain exactly 5000 images from each class.

2017年斯坦福大学经典课程cs231n的讲义，共16个pdf,每个pdf为一节课。pdf为高清英文原版，适合初学者入门深度学习

斯坦福cs231n课程笔记pdf版本，包括note，assignment,对了，是英文原版的