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Title: GitHub - gnehz/MachineLearning: Machine learning resources · GitHub

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Description: Machine learning resources. Contribute to gnehz/MachineLearning development by creating an account on GitHub.

Open Graph Description: Machine learning resources. Contribute to gnehz/MachineLearning development by creating an account on GitHub.

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READMEhttps://github.com/gnehz/MachineLearning
https://github.com/gnehz/MachineLearning#机器学习资源-machine-learning-resources
《机器学习》https://pan.baidu.com/s/1hscnaQC
《统计学习方法》https://pan.baidu.com/s/1dF2b4jf
《机器学习实战》https://pan.baidu.com/s/1gfzV7PL
https://www.jiqizhixin.com/articles/2018-06-21-6https://www.jiqizhixin.com/articles/2018-06-21-6
原Youtube地址需要梯子https://www.youtube.com/watch?v=xRJCOz3AfYY&list=PL2-dafEMk2A7mu0bSksCGMJEmeddU_H4D
百度网盘https://pan.baidu.com/s/1jICGJFg
课程http://speech.ee.ntu.edu.tw/~tlkagk/courses.html
题目https://www.kaggle.com/competitions?sortBy=deadline&group=all&page=1&pageSize=20&segment=gettingStarted
Kaggle介绍及入门解读https://zhuanlan.zhihu.com/p/25686876
可以用来练手的数据集https://www.kaggle.com/annavictoria/ml-friendly-public-datasets/notebook
机器学习经典教材《PRML》所有代码实现https://github.com/ctgk/PRML
机器学习算法Python实现https://github.com/lawlite19/MachineLearning_Python
深度学习(花书)中文版https://github.com/exacity/deeplearningbook-chinese
解析卷积神经网络—深度学习实践手册http://lamda.nju.edu.cn/weixs/book/CNN_book.html
一个简洁明了的时间序列处理(分窗、特征提取、分类)库：Seglearnhttps://dmbee.github.io/seglearn/index.html
计算机视觉这一年：这是最全的一份CV技术报告https://zhuanlan.zhihu.com/p/31430602
深度学习(花书)中文版https://github.com/exacity/deeplearningbook-chinese
深度学习最值得看的论文http://www.dlworld.cn/YeJieDongTai/4385.html
最全面的深度学习自学资源集锦http://dataunion.org/29975.html
Machine learning surveyshttps://github.com/metrofun/machine-learning-surveys/
快速入门TensorFlowhttps://github.com/aymericdamien/TensorFlow-Examples
自然语言处理数据集http://abunchofdata.com/datasets-for-natural-language-processing/
Learning Machine Learning? Six articles you don’t want to misshttp://www.ibmbigdatahub.com/blog/learning-machine-learning-six-articles-you-don-t-want-miss
Getting started with machine learning documented by githubhttps://github.com/collections/machine-learning
https://github.com/gnehz/MachineLearning#预备知识-prerequisite
学习知识与路线图https://metacademy.org/
MIT线性代数课堂笔记(中文)https://github.com/zlotus/notes-linear-algebra
概率与统计 The Probability and Statistics Cookbookhttp://statistics.zone/
Learn X in Y minuteshttps://learnxinyminutes.com/docs/python/
Python机器学习互动教程https://www.springboard.com/learning-paths/machine-learning-python/
Mastering Markdownhttps://guides.github.com/features/mastering-markdown/
R Tutorialhttp://www.cyclismo.org/tutorial/R/
http://ddl.escience.cn/f/IDkqhttp://ddl.escience.cn/f/IDkq
TensorFlowhttps://www.tensorflow.org/
Scikit-learnhttp://scikit-learn.org/
PyTorchhttp://pytorch.org/
Kerashttps://keras.io/
MXNethttp://mxnet.io/
相关资源大列表https://github.com/chinakook/Awesome-MXNet
Caffehttp://caffe.berkeleyvision.org/
Caffe2https://caffe2.ai/
Deeplearning4jhttps://deeplearning4j.org/
Neural Network Toolboxhttps://cn.mathworks.com/help/nnet/index.html
Deep Learning Toolboxhttps://cn.mathworks.com/matlabcentral/fileexchange/38310-deep-learning-toolbox
https://github.com/gnehz/MachineLearning#理论-theory
https://github.com/gnehz/MachineLearning#深度学习-deep-learning
强化学习 Reinforcement learninghttps://github.com/allmachinelearning/ReinforcementLearning
https://github.com/gnehz/MachineLearning#强化学习-reinforcement-learning
迁移学习 Transfer learninghttps://jindongwang.github.io/transferlearning/
https://github.com/gnehz/MachineLearning#迁移学习-transfer-learning
分布式学习系统 Distributed learning systemhttps://github.com/allmachinelearning/Deep-Learning-System-Design
https://github.com/gnehz/MachineLearning#分布式学习系统-distributed-learning-system
https://github.com/gnehz/MachineLearning#应用-applications
https://github.com/gnehz/MachineLearning#计算机视觉机器视觉-computer-vision--machine-vision
自然语言处理 Natural language procesinghttps://github.com/Nativeatom/NaturalLanguageProcessing
https://github.com/gnehz/MachineLearning#自然语言处理-natural-language-procesing
https://github.com/gnehz/MachineLearning#语音识别-speech-recognition
https://github.com/gnehz/MachineLearning#生物信息学-bioinfomatics
https://github.com/gnehz/MachineLearning#医疗-medical
行为识别 Activity recognitionhttps://github.com/jindongwang/activityrecognition
https://github.com/gnehz/MachineLearning#行为识别-activity-recognition
人工智能(多智能体) Artificial Intelligence(Multi-Agent)http://ddl.escience.cn/f/ILKI
https://github.com/gnehz/MachineLearning#人工智能多智能体-artificial-intelligencemulti-agent
https://github.com/gnehz/MachineLearning#文档-notes
综述文章汇总https://github.com/allmachinelearning/MachineLearning/blob/master/notes/survey_readme.md
近200篇机器学习资料汇总！https://zhuanlan.zhihu.com/p/26136757
机器学习入门资料https://github.com/allmachinelearning/MachineLearning/blob/master/notes/MLMaterials.md
MIT.Introduction to Machine Learninghttp://ddl.escience.cn/f/Iwtu
东京大学同学做的人机交互报告https://github.com/allmachinelearning/MachineLearning/blob/master/notes/FieldResearchinChina927-104.pdf
人机交互简介https://github.com/jindongwang/HCI
人机交互与创业论坛https://github.com/allmachinelearning/MachineLearning/blob/master/notes/%E4%BA%BA%E6%9C%BA%E4%BA%A4%E4%BA%92%E4%B8%8E%E5%88%9B%E4%B8%9A%E8%AE%BA%E5%9D%9B.md
职场机器学习入门https://github.com/allmachinelearning/MachineLearning/blob/master/notes/%E8%81%8C%E5%9C%BA-%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%85%A5%E9%97%A8.md
机器学习的发展历程及启示http://mt.sohu.com/20170326/n484898474.shtml
常用的距离和相似度度量https://github.com/allmachinelearning/MachineLearning/blob/master/notes/distance%20and%20similarity.md
https://github.com/gnehz/MachineLearning#课程与讲座-course-and-talk
https://github.com/gnehz/MachineLearning#机器学习-machine-learning
台湾大学应用深度学习课程https://www.csie.ntu.edu.tw/~yvchen/f106-adl/index.html
神经网络，机器学习，算法，人工智能等 30 门免费课程详细清单http://www.datasciencecentral.com/profiles/blogs/neural-networks-for-machine-learning
斯坦福机器学习入门课程https://www.coursera.org/learn/machine-learning
Neural Networks for Machine Learninghttps://www.coursera.org/learn/neural-networks
Stanford CS 229http://cs229.stanford.edu/materials.html
CMU 10-702 Statistical Machine Learninghttp://www.stat.cmu.edu/~larry/=sml/
CMU 10-715 Advanced Introduction to Machine Learninghttps://www.cs.cmu.edu/~epxing/Class/10715/
机器学习基石https://www.coursera.org/course/ntumlone
林轩田https://www.coursera.org/instructor/htlin
机器学习技法https://www.coursera.org/course/ntumltwo
林轩田https://www.coursera.org/instructor/htlin
Machine Learning for Data Analysishttps://www.coursera.org/learn/machine-learning-data-analysis
德国马普所智能系统研究所2013的机器学习暑期学校视频https://www.youtube.com/playlist?list=PLqJm7Rc5-EXFv6RXaPZzzlzo93Hl0v91E
我们一起开始机器学习吧https://www.zhihu.com/lives/792423196996546560
机器学习入门之特征工程https://www.zhihu.com/lives/819543866939174912
https://github.com/gnehz/MachineLearning#深度学习-machine-learning
CS231n系列深度学习课程http://cs231n.stanford.edu/
这里https://zhuanlan.zhihu.com/p/21930884
CS224n: Natural Language Processinghttp://cs224n.stanford.edu
https://github.com/gnehz/MachineLearning#强化学习-machine-learning
CS 294 Deep Reinforcement Learning, Fall 2017http://rll.berkeley.edu/deeprlcourse/
UCL Course on RLhttp://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html
CS234: Reinforcement Learninghttp://web.stanford.edu/class/cs234/index.html
https://github.com/gnehz/MachineLearning#相关书籍-reference-book
Hands on Machine Learning with Scikit-learn and Tensorflowhttps://my.pcloud.com/publink/show?code=XZ9ev77Zk2l6xcMtfIhHm7mRKAYhISb6sl3k
The Elements of Statistical Learning(英文第二版),The Elements of Statistical Learning.pdfhttp://ddl.escience.cn/ff/emZH
机器学习https://book.douban.com/subject/26708119/
统计学习方法https://book.douban.com/subject/10590856/
一些Kindle读物http://ddl.escience.cn/f/IwWE
数学https://mega.nz/#F!WVAlGL6B!mqIjYoTjiQnO4jBGVLRIWA
Packt每日限免电子书精选http://ddl.escience.cn/f/IS4a
https://github.com/gnehz/MachineLearning#其他-miscellaneous
机器学习日报http://forum.ai100.com.cn/
机器之心https://www.jiqizhixin.com/
集智社区https://jizhi.im/index
https://github.com/gnehz/MachineLearning#如何加入-how-to-contribute
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https://github.com/gnehz/MachineLearning#如何开始项目协同合作
快速了解github协同工作http://hucaihua.cn/2016/12/02/github_cooperation/
及时更新fork项目https://jinlong.github.io/2015/10/12/syncing-a-fork/
贡献者 Contributorshttps://github.com/allmachinelearning/MachineLearning/blob/master/contributors.md
https://github.com/gnehz/MachineLearning#贡献者-contributors
allmachinelearning.github.io/MachineLearning/https://allmachinelearning.github.io/MachineLearning/
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