搜索方法合集，优化算法大全，大师之作，本书提供了大量的完整的先进的优化搜索算法，希望能给读者带来帮助和启示

Understanding Learning Rates and How It Improves Performance in Deep Learning This post is an attempt to document my understanding on the following topic: What is the learning rate? What is it’s signibcance? How does one systematically arrive at a good learning rate? Why do we change the learning rate during training? How do we deal with learning rates when using pretrained model?

This is one of my most favorite books that teache deep learning from the very basic to advance level. The book does not emphasize on mathematics but explains the logic behind each deep learning algorithm in plain English. Even if you are the new guy in deep learning or you are already at an advance level, this book is for you. Vol 2 will be coming shortly

这个资源是一个拥有完整代码与测试数据的k-means算法文件。距离计算方式中，欧式距离、余弦距离均实现了，且可作为程序参数供用户自由选择；两份数据集均进行了聚类，聚类结果由程序自动保存到txt文件中；聚类结果中包含SSE值。

chapter2_PyTorch-Basics chapter3_NN chapter4_CNN chapter5_RNN chapter6_GAN chapter7_RL chapter8_PyTorch-Advances chapter9_Computer-Vision chapter10_Natural-Language-Process

2015年英国牛津大学karen simonyan深度学习的vgg模型论文原文

吴恩达在coursera上免费的斯坦福deep learning课程的同步资料，包含完整的matlab代码与PDF文档说明

Deep learning for computer vision with python-starter bundle(pdf+code+dataset) by Adrian at PyImageSearch

Hands on Machine Learning with Scikit Learn and TensorFlow 英文原版 彩色配图

这是一篇关于深度学习应用于图像处理的高质量文献，其中的方法比较新颖。