DL基础

1. CS231n课程总结
   总结出了每一节课程的精华要点。
2. CSDN博客Tensorflow实战学习笔记、代码、机器学习进阶系列
3. 《机器学习基石》和《机器学习技法》课程笔记
4. 机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归
5. 13张动图，彻底看懂马尔科夫链、PCA和条件概率
6. Deep Learning - From Basics to Practice notebook 代码
7. 手动实现NN中各个模块
8. Segnet, FCN, UNet and other models in Keras.
9. MATLAB library for stochastic optimization algorithms
10. A Python Toolbox for Ensemble Learning and Visualisation
11. 机器学习100天
12. facebook AI 研究院免费课：Intro to Deep Learning with PyTorch
13. Deep Learning and Reinforcement Learning Summer School, Toronto 2018

Domain knowledge总结

1. GAN医学图像处理相关资料大列表
2. 基于深度学习的目标检测算法综述
   综述1
3. 回归模型优缺点总结
4. 机器学习项目完整解决流程演练
5. pytorch写的sklearn库

50%+ Faster, 50%+ less RAM usage, GPU support re-written Sklearn

6. Understanding and diagnosing your machine-learning models

开源论文

1. Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer’s Disease (MICCAI 2018 MLCN workshop) (Code)
2. Norm matters: efficient and accurate normalization schemes in deep networks (paper) (code)