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Title: 机器学习资源 Machine learning Resources | MachineLearning

Open Graph Title: 机器学习资源 Machine learning Resources

X Title: 机器学习资源 Machine learning Resources

Description: Machine learning resources

Open Graph Description: Machine learning resources

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Links:

Skip to the content.https://allmachinelearning.github.io/MachineLearning/#content
View on GitHubhttps://github.com/allmachinelearning/MachineLearning
《机器学习》https://pan.baidu.com/s/1hscnaQC
《神经网络与深度学习》https://mp.weixin.qq.com/s?__biz=MzIwOTc2MTUyMg==&mid=2247488439&idx=1&sn=df51b67ac2a42fe1a8417a7e4d308b8b&chksm=976fb62aa0183f3c8cfbfcf2c1613aa3a168f782bc5b439aa2a5db9574a33f678a081a1d24a5&mpshare=1&scene=1&srcid=0409hgaWjfxz2LzGtniTpAKh&key=12a4c5f4665589b6914fa6a60a7fe4bd6a4fc4855ac8967b945678646a60c26482467697a46b85e85c7a6a7d564aac41d6c0312307a7f95ba299d3b3cf8433f9a159f999d9484534452672dbdd9fd270&ascene=1&uin=NjMzMjQzMTYw&devicetype=Windows+10&version=62060739&lang=zh_CN&pass_ticket=CIhr0hAvTnkZIvwFNRQ2%2BWhir8OVCkCt9tarvfIPS5SWtyyQKMLGOBt%2BItSffrll
《统计学习方法》https://pan.baidu.com/s/1dF2b4jf
书中的代码实现https://github.com/WenDesi/lihang_book_algorithm
《机器学习实战》https://pan.baidu.com/s/1gfzV7PL
课程http://speech.ee.ntu.edu.tw/~tlkagk/courses.html
书的主页http://jd92.wang/tlbook
Domain adaptationhttps://github.com/jindongwang/transferlearning/tree/master/code/DeepDA
Domain generalizationhttps://github.com/jindongwang/transferlearning/tree/master/code/DeepDG
更多代码https://github.com/jindongwang/transferlearning
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
吴恩达新书：Machine Learning Yearning中文版https://pan.baidu.com/s/10kosKx6rDguS4tPejY-fRw
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
深度学习 Deep learninghttps://github.com/ChristosChristofidis/awesome-deep-learning
强化学习 Reinforcement learninghttps://github.com/aikorea/awesome-rl
迁移学习 Transfer learninghttps://github.com/jindongwang/transferlearning
分布式学习系统 Distributed learning systemhttps://github.com/theanalyst/awesome-distributed-systems
计算机视觉/机器视觉 Computer vision / machine visionhttps://github.com/jbhuang0604/awesome-computer-vision
自然语言处理 Natural language procesinghttps://github.com/Nativeatom/NaturalLanguageProcessing
生物信息学 Bioinfomaticshttps://github.com/danielecook/Awesome-Bioinformatics
行为识别 Activity recognitionhttps://github.com/jindongwang/activityrecognition
多智能体 Multi-Agenthttp://ddl.escience.cn/f/ILKI
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/
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
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
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
CS229课程讲义的中文翻译https://github.com/Kivy-CN/Stanford-CS-229-CN
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
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
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
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
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
UPLOADhttps://my.pcloud.com/#page=puplink&code=4e9Z0Vwpmfzvx0y2OqTTTMzkrRUz8q9V
DOWNLOADhttps://my.pcloud.com/publink/show?code=kZWtboZbDDVguCHGV49QkmlLliNPJRMHrFX
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
MachineLearninghttps://github.com/allmachinelearning/MachineLearning
allmachinelearninghttps://github.com/allmachinelearning
GitHub Pageshttps://pages.github.com

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