https://github.com/roboticcam/machine-learning-notes/blob/master/README.md
Practice and tutorial-style notebooks covering wide variety of machine learning techniques https://github.com/tirthajyoti/PythonMachineLearning
https://github.com/dennybritz/deeplearning-papernotes Summaries and notes on Deep Learning research papers http://www.kdd.org/kdd2016/papers/files/rpp0426-feiA.pdf Learning Cumulatively to Become More Knowledgeable http://xueshu.baidu.com/s?wd=paperuri%3A%2813855fb298f0c3e47be0b5abe018d78a%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Farxiv.org%2Fpdf%2F1705.00251&ie=utf-8&sc_us=1318122486657168244 Lifelong Learning CRF for Supervised Aspect Extraction
https://arxiv.org/pdf/1804.04577.pdf Feature-Based Aggregation and Deep Reinforcement Learning a survey and some implementations
The most cited deep learning papers: https://github.com/terryum/awesome-deep-learning-papers
https://mp.weixin.qq.com/s?__biz=MzU2OTA0NzE2NA==&mid=2247493879&idx=1&sn=d6c17bbbd5a76a32554817dd564ccfad&chksm=fc8609e4cbf180f216f64d0deb82a3de70ba2cd83003d049cb1a1606bed49c8a6c4c4fe9288c&mpshare=1&scene=24&srcid=07311emVxxDtKx5YPJtyiVuH#rd 【2018最新版】 200个最好的与机器学习、自然语言处理相关教程
https://github.com/Developer-Y/cs-video-courses List of Computer Science courses with video lectures. https://github.com/ChristosChristofidis/awesome-deep-learning A curated list of awesome Deep Learning tutorials, projects and communities.
https://github.com/jindongwang/transferlearning-tutorial 《迁移学习简明手册》 https://github.com/jindongwang/transferlearning Everything about Transfer Learning and Domain Adaptation https://github.com/allmachinelearning/MachineLearning Machine learning resource https://github.com/khanhnamle1994/computer-vision Programming Assignments and Lectures for Stanford's CS 231: Convolutional Neural Networks for Visual Recognition http://cs231n.stanford.edu/ https://www.zhihu.com/question/64021205 计算机视觉中video understanding领域有什么研究方向和比较重要的成果？ https://www.zhihu.com/question/67257036 计算机视觉方向博士如何做好科研？
https://github.com/pytorch/vision/ Datasets, Transforms and Models specific to Computer Vision https://github.com/fengdu78/Coursera-ML-AndrewNg-Notes 吴恩达老师的机器学习课程个人笔记
https://github.com/fengdu78/deeplearning.ai（吴恩达老师的深度学习课程笔记及资源） https://github.com/artix41/awesome-transfer-learning Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.) https://github.com/apachecn/hands_on_Ml_with_Sklearn_and_TF OReilly Hands On Machine Learning with Scikit Learn and TensorFlow (Sklearn与TensorFlow机器学习实用指南)
https://github.com/aikorea/awesome-rl#papers--thesis Reinforcement learning resources curated http://aikorea.org/awesome-rl
https://github.com/tryolabs/luminoth Deep Learning toolkit for Computer Vision https://luminoth.ai https://github.com/wichtounet/dll Deep Learning Library (DLL) for C++ (ANNs, CNNs, RBMs, DBNs...) https://github.com/intel-analytics/BigDL/ BigDL: Distributed Deep Learning Library for Apache Spark https://bigdl-project.github.io/