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机器学习相关网址

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机器学习相关网址

作者:凯鲁嘎吉 - 博客园 http://www.cnblogs.com/kailugaji/

1. 个人博客

Free Mind

http://freemind.pluskid.org/ 

Junhao Hua 博客 | huajh7‘s Blog 

http://blog.huajh7.com/ 

Jorbe‘s Blog | Never say never 

http://jorbe.sinaapp.com/ 

刘未鹏 | Mind Hacks – 思维改变生活 

http://mindhacks.cn/ 

lucky6.coding.me 

http://lucky6.coding.me/ 

科学空间|Scientific Spaces 

https://spaces.ac.cn/ 

Unsupervised learning: The curious pupil | DeepMind 

https://deepmind.com/blog/article/unsupervised-learning 

一些关于机器学习的网站总结 | LiXiang  NLP

http://www.leexiang.com/a-summary-of-some-websites-about-machine-learning 

标点符 – 技术,思考,人生  聚类、相似度度量,机器学习

https://www.biaodianfu.com/ 

Math ∩ Programming 

https://jeremykun.com/

The Clever Machine | Topics in Computational Neuroscience & Machine Learning  计算神经科学与机器学习博客

https://theclevermachine.wordpress.com/ 

卢明冬的博客 | 自由思考的空间 

https://lumingdong.cn/

SHEN‘s BLOG 

https://shenxiaohai.me/ 

2. 相关书籍

Data Mining and Analysis Main/Book Resources 

http://www.dataminingbook.info/pmwiki.php/Main/BookResources 

Introduction - Computer Graphics from scratch - Gabriel Gambetta 

https://www.gabrielgambetta.com/computer-graphics-from-scratch/introduction.html 

Gaussian Processes for Machine Learning: Contents 

http://www.gaussianprocess.org/gpml/chapters/

机器学习原理 

https://www.cntofu.com/book/85/index.html

Mathematics for Machine Learning | Companion webpage to the book “Mathematics for Machine Learning”. Copyright 2019 by Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong. To be published by Cambridge University Press. 

https://mml-book.github.io/ 

数据常青藤 | 人工智能、机器学习、深度学习、神经网络、模式识别、自然语言处理、图像识别…数据智能工作才是数据的未来! 

http://www.dataivy.cn/

Machine Learning: The Art and Science of Algorithms that Make Sense of Data by Peter Flach 

https://mlbook.cs.bris.ac.uk/

3. 计算机课程

工程数值分析| 电气与计算机工程系| 滑铁卢大学 

https://ece.uwaterloo.ca/~dwharder/NumericalAnalysis/ 

Machine Learning - complete course notes 

http://www.holehouse.org/mlclass/ 

Stephen P. Boyd  凸优化,优化问题,近端算法等运筹学知识

https://web.stanford.edu/~boyd/ 

Level Set Method: an Explanation 

http://profs.etsmtl.ca/hlombaert/levelset/ 

Carlos Rodriguez‘s Home Page  概率论:科学的逻辑

https://omega0.xyz/omega8008/ 

Max Welling‘s Classnotes in Machine Learning

https://www.ics.uci.edu/~welling/classnotes/classnotes.html 

Gatsby Computational Neuroscience 

http://www.gatsby.ucl.ac.uk/teaching/courses/index.html 

Frank Wood, Associate Professor, (Information) Engineering, Oxford 无监督学习

http://www.robots.ox.ac.uk/~fwood/teaching/C19_hilary_2016_2017/index.html 

Yee Whye Teh  统计机器学习,贝叶斯

https://www.stats.ox.ac.uk/~teh/ 

OxCSML : Groups : Machine Learning  统计机器学习

http://csml.stats.ox.ac.uk/learning/

Applied Mathematics for Computer Science

http://www.cad.zju.edu.cn/home/zhx/csmath/doku.php?id=start 

4. 数据集

各领域公开数据集下载 - 知乎 

https://zhuanlan.zhihu.com/p/25138563 

常见公开数据集(持续更新...) - 简书 

https://www.jianshu.com/p/13420e9cf532 

100款机器学习数据集 - haoji007的博客 - CSDN博客 

https://blog.csdn.net/haoji007/article/details/81020229 

Datasets for Data Science and Machine Learning 

https://elitedatascience.com/datasets 

人工智能机器学习数据集收集整理--持续更新中 - 简书 

https://www.jianshu.com/p/8c7c1af7d593 

CVonline: Image Databases 

http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm 

5. 其他

林子雨编著-大数据软件安装和编程实践指南_厦门大学数据库实验室 

http://dblab.xmu.edu.cn/post/7586/ 

Peer to Peer (P2P,对等网络) 综述 

http://www.intsci.ac.cn/users/luojw/P2P/ 

GitHub - jindongwang/transferlearning: Everything about Transfer Learning and Domain Adaptation--迁移学习 

https://github.com/jindongwang/transferlearning 

在线 LaTeX 公式编辑器 

https://www.codecogs.com/latex/eqneditor.php 

Wolfram MathWorld: The Web‘s Most Extensive Mathematics Resource  线上数学百科全书

http://mathworld.wolfram.com/ 

arXiv Analytics  直接看到最新的arXiv文章

http://arxitics.com/ 

How to Write Guide: Sections of the Paper 

http://abacus.bates.edu/~ganderso/biology/resources/writing/HTWsections.html 

计算机视觉方面博客及代码 - 知乎 

https://zhuanlan.zhihu.com/p/30104462 

Codes and Datasets for Feature Learning 

http://www.cad.zju.edu.cn/home/dengcai/Data/data.html 

机器学习相关网址

原文:https://www.cnblogs.com/kailugaji/p/11459324.html

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