https://github.com/howie6879/mlhub123
机器学习&深度学习网站资源汇总（Machine Learning Resources）
https://github.com/howie6879/mlhub123
deep-learning machine-learning
Last synced: about 2 months ago
JSON representation
机器学习&深度学习网站资源汇总（Machine Learning Resources）
- Host: GitHub
- URL: https://github.com/howie6879/mlhub123
- Owner: howie6879
- License: mit
- Created: 2018-07-20T02:35:35.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2023-03-13T02:23:36.000Z (about 2 years ago)
- Last Synced: 2025-01-20T23:15:32.347Z (3 months ago)
- Topics: deep-learning, machine-learning
- Homepage: https://www.mlhub123.com/
- Size: 80.1 KB
- Stars: 1,064
- Watchers: 33
- Forks: 237
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
- [mlhub123](#mlhub123)
- [导航](#导航)
- [新闻资讯](#新闻资讯)
- [工具服务](#工具服务)
- [社区交流](#社区交流)
- [优质博文](#优质博文)
- [资源检索](#资源检索)
- [比赛实践](#比赛实践)
- [资源](#资源)
- [课程学习](#课程学习)
- [资源收集](#资源收集)
- [开源书籍](#开源书籍)
- [实战项目](#实战项目)
- [方法论](#方法论)
- [文档](#文档)
- [Python](#python)
- [C \& C++](#c--c)
# mlhub123
机器学习网站导航以及资源，欢迎**PR提供资源**：
- 网站：[https://www.mlhub123.com/](https://www.mlhub123.com/)
- 进微信群交流：备注mlhub进群 - [mlhub](https://ws1.sinaimg.cn/large/007i3XCUgy1fwgr8qhjz7j306506faag.jpg)
- Telegram群组：[欢迎加入](https://t.me/joinchat/F6XKShFSdCUHuo5Rvoj4Jg)，资源多多~
## 导航
### 新闻资讯
- [Analytics Vidhya](https://www.analyticsvidhya.com/blog/?from=www.mlhub123.com): 为数据科学专业人员提供基于社区的知识门户
- [Distill](https://distill.pub/?from=www.mlhub123.com): 展示机器学习的最新文章
- [Google News](https://news.google.com/topics/CAAqIggKIhxDQkFTRHdvSkwyMHZNREZvZVdoZkVnSmxiaWdBUAE?hl=en-US&gl=US&ceid=US%3Aen?from=www.mlhub123.com): Google News Machine learning
- [kdnuggets](https://www.kdnuggets.com/?from=www.mlhub123.com): Machine Learning, Data Science, Big Data, Analytics, AI
- [MIT News](http://news.mit.edu/topic/machine-learning?from=www.mlhub123.com): Machine learning | MIT News
- [机器之心](https://www.jiqizhixin.com?from=www.mlhub123.com): 机器之心 | 全球人工智能信息服务
- [雷锋网](https://www.leiphone.com/?from=www.mlhub123.com): 雷锋网 | 读懂智能，未来
- [数据分析网](https://www.afenxi.com?from=www.mlhub123.com): 数据分析网 - 大数据学习交流第一平台
- [知乎主题](https://www.zhihu.com/topic/19559450/hot?from=www.mlhub123.com): 知乎机器学习热门主题
- [专知](http://www.zhuanzhi.ai?from=www.mlhub123.com): AI知识分发服务平台
- [aminer](https://www.aminer.cn/research_report/articlelist?from=www.mlhub123.com): 科技资讯
### 工具服务
- [chatgpt](https://ai.com/?from=www.mlhub123.com): OpenAI开发的人工智能聊天机器人程序
- [codeocean](https://codeocean.com/?from=www.mlhub123.com): 可重现性代码共享平台
- [colab](https://colab.research.google.com/?from=www.mlhub123.com): 免费使用GPU的在线工作平台
- [ECharts](https://echarts.apache.org/?from=www.mlhub123.com): 使用JavaScript实现的开源可视化库
- [excalidraw](https://excalidraw.com/?from=www.mlhub123.com): 绘图软件
- [drawio](https://draw.io?from=www.mlhub123.com) 开源免费的绘图工具
- [Khroma](http://khroma.co/?from=www.mlhub123.com): 人工智能配色网站
### 社区交流
- [AIQ](http://www.6aiq.com/?from=www.mlhub123.com): 机器学习大数据技术社区
- [DataTau](https://www.datatau.com?from=www.mlhub123.com): 人工智能领域的Hacker News
- [MathOverflow](https://mathoverflow.net?from=www.mlhub123.com): 数学知识问答社区
- [Medium](https://medium.com/?from=www.mlhub123.com): 一个涵盖人工智能、机器学习和深度学习相关领域的自由、开放平台
- [PaperWeekly](http://www.paperweekly.site?from=www.mlhub123.com): 一个推荐、解读、讨论和报道人工智能前沿论文成果的学术平台
- [Quora](https://www.quora.com/pinned/Machine-Learning?from=www.mlhub123.com): Quora | 机器学习主题
- [Reddit](https://www.reddit.com/r/MachineLearning/?from=www.mlhub123.com): Reddit | 机器学习板块
- [ShortScience](http://www.shortscience.org?from=www.mlhub123.com): 用最简单的篇幅去概况科学著作
- [Twitter](https://twitter.com/StatMLPapers?from=www.mlhub123.com): Twitter | 机器学习论文版块
### 优质博文
- [Google AI Blog](https://ai.googleblog.com/?from=www.mlhub123.com): 谷歌AI博客
- [handong1587](https://handong1587.github.io/?from=www.mlhub123.com): 深度学习各个方向资源汇总，及各大顶级会议/期刊资源
- [Machine Learning Mastery](https://machinelearningmastery.com/blog?from=www.mlhub123.com): 帮助开发人员使用机器学习的知识解决复杂的问题
- [paralleldots](https://blog.paralleldots.com/?from=www.mlhub123.com)：一个提供随时可用的一流AI解决方案的博客
- [tornadomeet的博客](https://www.cnblogs.com/tornadomeet/archive/2012/06/24/2560261.html?from=www.mlhub123.com): 很详细的ML&DL学习博客
- [wildml](http://www.wildml.com/?from=www.mlhub123.com)：Artificial Intelligence, Deep Learning, and NLP
- [爱可可-爱生活](https://weibo.com/fly51fly?topnav=1&wvr=6&topsug=1?from=www.mlhub123.com): 知名互联网资讯博主
- [超智能体](https://zhuanlan.zhihu.com/YJango?from=www.mlhub123.com): 分享最通俗易懂的深度学习教程
- [人工智能笔记](https://zhuanlan.zhihu.com/ainote?from=www.mlhub123.com): 人工智能从入门到AI统治世界
### 资源检索
- [arXiv](https://arxiv.org?from=www.mlhub123.com): 康奈尔大学运营的学术预印本发布的平台
- [Arxiv Sanity](http://www.arxiv-sanity.com/?from=www.mlhub123.com): 论文查询推荐
- [bifrost](https://datasets.bifrost.ai/?from=www.mlhub123.com): 提供人物、自动驾驶汽车、零售、无人机等六大类别数据集检索
- [connected papers](https://www.connectedpapers.com/?from=www.mlhub123.com): 用可视化的形式发现&浏览论文
- [Hugging Face](https://huggingface.co/?from=www.mlhub123.com): 机器学习界的github，提供预训练模型和数据集等资源
- [iData](https://www.cn-ki.net/?from=www.mlhub123.com): iData-知识检索
- [lexica](https://lexica.art/?from=www.mlhub123.com): 超过10M + Stable Diffusion 图像和 Prompts
- [NLP Index](https://index.quantumstat.com/?from=www.mlhub123.com): 实用的NLP索引工具
- [Papers with Code](https://paperswithcode.com/?from=www.mlhub123.com): 将论文与开源代码实现结合
- [phind](https://phind.com/?from=www.mlhub123.com): The AI search engine for developers
- [SCI-HUB](https://sci-hub.ru/?from=www.mlhub123.com): 找论文必备
- [Semantic Scholar](https://www.semanticscholar.org/?from=www.mlhub123.com): 致力于解决信息超载的学术文献搜索引擎
### 比赛实践
- [DataCastle](http://www.pkbigdata.com/?from=www.mlhub123.com): 中国领先的数据科学竞赛平台
- [DataFountain](http://www.datafountain.cn/#/?from=www.mlhub123.com): DF,CCF指定专业大数据竞赛平台
- [Kaggle](https://www.kaggle.com/?from=www.mlhub123.com): 为数据科学家提供举办机器学习竞赛
- [KDD-CUP](http://www.kdd.org/kdd-cup?from=www.mlhub123.com): 国际知识发现和数据挖掘竞赛
- [赛氪网](http://www.saikr.com/?from=www.mlhub123.com): 汇集以高校竞赛为主，活动、社区为辅的大学生竞赛活动平台
- [天池大数据](https://tianchi.aliyun.com/?from=www.mlhub123.com): 大数据竞赛、大数据解决方案、数据科学家社区、人工智能、机器学习
## 资源
### 课程学习
- [data-science-complete-tutorial](https://github.com/zekelabs/data-science-complete-tutorial?from=www.mlhub123.com): 数据科学完整入门指南
- [David Silver](https://v.youku.com/v_show/id_XMjcwMDQyOTcxMg==.html?spm=a2h0j.11185381.listitem_page1.5!4~A&&f=49376145?from=www.mlhub123.com): David Silver 深度强化学习课程
- [fast.ai](http://www.fast.ai/?from=www.mlhub123.com): Making neural nets uncool again
- [hanbt](https://www.zybuluo.com/hanbingtao/note/433855?from=www.mlhub123.com): 零基础入门深度学习，深入浅出，很不错的入门教程
- [Juicy Big Data](https://github.com/datawhalechina/juicy-bigdata?from=www.mlhub123.com): Datawhale大数据处理导论教程
- [liuyubobobo](https://coding.imooc.com/class/169.html?from=www.mlhub123.com): Python3 入门机器学习
- [Metacademy](https://metacademy.org/?from=www.mlhub123.com): 知识点检索并画出通向这个知识点的知识图谱
- [MLEveryday](https://github.com/MLEveryday?from=www.mlhub123.com): machine learning everyday
- [Siraj Raval：时序预测](https://www.kaggle.com/learn/time-series-with-siraj?from=www.mlhub123.com): Kaggle免费课程：时序预测
- [Two Minute Papers](https://www.youtube.com/channel/UCbfYPyITQ-7l4upoX8nvctg?from=www.mlhub123.com): YouTube | 最简短的语言概况最新的热点论文
- [YSDA nlp_course](https://github.com/yandexdataschool/nlp_course?from=www.mlhub123.com): YSDA course in Natural Language Processing
- [3Blue1Brown](https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw?from=www.mlhub123.com): YouTube | 数学基础频道
- [3Blue1Brown 中文](http://space.bilibili.com/88461692/#/?from=www.mlhub123.com): Bilibili | 数学基础频道
- [谷歌：机器学习速成课程](https://developers.google.cn/machine-learning/crash-course/?from=www.mlhub123.com): Google制作的节奏紧凑、内容实用的机器学习简介课程
- [李宏毅](https://speech.ee.ntu.edu.tw/~hylee/index.php?from=www.mlhub123.com): 李宏毅深度学习课程
- [林轩田](https://www.bilibili.com/video/av12469267?from=www.mlhub123.com): 机器学习技法
- [邱锡鹏（复旦大学）](https://github.com/nndl/nndl.github.io?from=www.mlhub123.com): 神经网络与深度学习
- [人工智能公开课合集](https://study.163.com/series/1001461001.htm?from=www.mlhub123.com)人工智能国内外顶尖公开课系列
- [吴恩达](https://study.163.com/course/introduction/1210076550.htm?from=www.mlhub123.com): 机器学习课程
- [吴恩达](https://mooc.study.163.com/smartSpec/detail/1001319001.htm?from=www.mlhub123.com): 深度学习课程
- [徐亦达](https://github.com/roboticcam/machine-learning-notes?from=www.mlhub123.com): 徐亦达老师机器学习课程
- [张子豪（同济）](https://github.com/TommyZihao/zihao_course/?from=www.mlhub123.com): 同济子豪兄的公开课：机器学习+计算机视觉+论文精读
### 资源收集
- [awesome-machine-learning-cn](https://github.com/jobbole/awesome-machine-learning-cn?from=www.mlhub123.com): 机器学习资源大全中文版，包括机器学习领域的框架、库以及软件
- [awesome-public-datasets](https://github.com/awesomedata/awesome-public-datasets?from=www.mlhub123.com): 各领域公开数据集下载
- [Coursera-ML-AndrewNg-Notes](https://github.com/fengdu78/Coursera-ML-AndrewNg-Notes?from=www.mlhub123.com): 吴恩达老师的机器学习课程个人笔记
- [daily-paper-computer-vision](https://github.com/amusi/daily-paper-computer-vision?from=www.mlhub123.com): 记录每天整理的计算机视觉/深度学习/机器学习相关方向的论文
- [DeepLearning-500-questions](https://github.com/scutan90/DeepLearning-500-questions?from=www.mlhub123.com)：深度学习500问
- [deeplearning_ai_books](https://github.com/fengdu78/deeplearning_ai_books?from=www.mlhub123.com): 吴恩达老师的深度学习课程笔记及资源
- [Deep-Learning-Papers-Reading-Roadmap](https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap?from=www.mlhub123.com): 深度学习论文阅读路线图
- [funNLP](https://github.com/fighting41love/funNLP?from=www.mlhub123.com)：中文语料库资源收集项目
- [FunRec](https://datawhalechina.github.io/fun-rec/#/?from=www.mlhub123.com): 推荐算法基础+实战+面经
- [Getting Started in Computer Vision Research](https://sites.google.com/site/mostafasibrahim/research/articles/how-to-start?from=www.mlhub123.com)：计算机视觉研究入门全指南
- [lihang_book_algorithm](https://github.com/WenDesi/lihang_book_algorithm?from=www.mlhub123.com): 《统计学习方法》算法python实现
- [Machine Learning、Deep Learning](https://github.com/ty4z2008/Qix/blob/master/dl.md?from=www.mlhub123.com): ML&DL资料
- [MachineLearning_Python](https://github.com/lawlite19/MachineLearning_Python?from=www.mlhub123.com): 机器学习算法python实现
- [Machine_Learning_Study_Path](https://github.com/linxid/Machine_Learning_Study_Path?from=www.mlhub123.com)：机器学习过程中所看的书，视频和源码
- [ml_cheatsheet](https://github.com/remicnrd/ml_cheatsheet?from=www.mlhub123.com)：机器学习算法速查手册
- [ml_tutorials](https://github.com/MorvanZhou/tutorials?from=www.mlhub123.com): 机器学习相关教程
- [NLP-progress](https://github.com/sebastianruder/NLP-progress?from=www.mlhub123.com)：跟踪NLP各项技术的state-of-the-art进展
- [paper-qa](https://github.com/whitead/paper-qa?from=www.mlhub123.com): 用GPT-3来解读论文的开源项目
- [paper-reading](https://github.com/mli/paper-reading?from=www.mlhub123.com): 深度学习经典、新论文逐段精读
- [papers-we-love](https://github.com/papers-we-love/papers-we-love?from=www.mlhub123.com): 阅读、讨论和学习计算机科学学术论文的社区
- [100-Days-Of-ML-Code 英文版](https://github.com/Avik-Jain/100-Days-Of-ML-Code?from=www.mlhub123.com)：100 Days of Machine Learning Coding as proposed by Siraj Raval
- [100-Days-Of-ML-Code 中文版](https://github.com/MLEveryday/100-Days-Of-ML-Code?from=www.mlhub123.com)：100-Days-Of-ML-Code 中文版
- [系统学习机器学习](https://www.zhihu.com/question/266291909?from=www.mlhub123.com): 系统学习机器学习
- [周志华 - 机器学习](https://github.com/Vay-keen/Machine-learning-learning-notes?from=www.mlhub123.com): 周志华《机器学习》笔记
### 开源书籍
- [AiLearning](https://github.com/apachecn/MachineLearning?from=www.mlhub123.com): AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
- [deeplearningbook-chinese](https://github.com/exacity/deeplearningbook-chinese?from=www.mlhub123.com): 深度学习中文版
- [动手学深度学习](https://github.com/d2l-ai/d2l-zh?from=www.mlhub123.com): 《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被60多个国家的400多所大学用于教学。
- [deep_learning_cookbook](https://github.com/DOsinga/deep_learning_cookbook?from=www.mlhub123.com): 深度学习手册
- [hands_on_Ml_with_Sklearn_and_TF](https://github.com/apachecn/hands_on_Ml_with_Sklearn_and_TF?from=www.mlhub123.com): Sklearn与TensorFlow机器学习实用指南
- [Interpretable Machine Learning](https://christophm.github.io/interpretable-ml-book/?from=www.mlhub123.com): 一份指南，教你如何构建具有可解释性的黑盒模型
- [Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com/index.html?from=www.mlhub123.com): 深度学习开源书籍
- [Neural Networks and Deep Learning](https://github.com/zhanggyb/nndl?from=www.mlhub123.com): 深度学习开源书籍 - 中文
- [PythonDataScienceHandbook](https://github.com/jakevdp/PythonDataScienceHandbook?from=www.mlhub123.com): Python数据科学手册
- [TensorFlow-Course](https://github.com/open-source-for-science/TensorFlow-Course?from=www.mlhub123.com): 简单易学的TensorFlow教程
- [简单粗暴 TensorFlow 2](https://tf.wiki?from=www.mlhub123.com): 一本简明的 TensorFlow 2 入门指导手册
### 实战项目
- [face_recognition](https://github.com/ageitgey/face_recognition?from=www.mlhub123.com): 世界上最简单的人脸识别库
- [style2paints](https://github.com/lllyasviel/style2paints?from=www.mlhub123.com): 线稿自动上色
### 方法论
- [face_recognition](https://space.bilibili.com/344849038/dynamic?from=www.mlhub123.com): 学习观
- [tuning_playbook](https://github.com/google-research/tuning_playbook?from=www.mlhub123.com): 聚焦超参数调整的深度学习调优手册
## 文档
### Python
- [Caffe](http://caffe.berkeleyvision.org/?from=www.mlhub123.com): 一个基于表达式，速度和模块化原则创建的深度学习框架
- [Caffe2](https://caffe2.ai/docs/getting-started.html?platform=windows&configuration=compile?from=www.mlhub123.com): Caffe2官方文档
- [Chainer](https://docs.chainer.org/en/stable/?from=www.mlhub123.com): 基于Python的独立的深度学习模型开源框架
- [CNTK](https://docs.microsoft.com/en-us/cognitive-toolkit/?from=www.mlhub123.com): CNTK官方文档
- [Gensim](https://radimrehurek.com/gensim/index.html?from=www.mlhub123.com): 包含可扩展的统计语义，分析纯文本文档的语义结构，以及检索相似语义的文档等功能
- [Keras](https://keras.io/?from=www.mlhub123.com): Keras官方文档
- [Matplotlib](https://matplotlib.org/stable/tutorials/index.html?from=www.mlhub123.com): Matplotlib官方文档
- [MXNet](https://mxnet.incubator.apache.org/api/python/docs/tutorials/?from=www.mlhub123.com): MXNet官方文档
- [NumPy](http://www.numpy.org/?from=www.mlhub123.com): NumPy官方文档
- [pandas](http://pandas.pydata.org/pandas-docs/stable/?from=www.mlhub123.com): pandas官方文档
- [PyBrain](http://pybrain.org/docs/?from=www.mlhub123.com): 一个模块化的Python机器学习库
- [PyTorch](https://pytorch.org/tutorials/?from=www.mlhub123.com): PyTorch官方文档
- [Seaborn](https://seaborn.pydata.org/?from=www.mlhub123.com): statistical data visualization
- [scikit-learn](http://scikit-learn.org/stable/documentation.html?from=www.mlhub123.com): scikit-learn官方文档
- [Statsmodels](http://www.statsmodels.org/stable/index.html?from=www.mlhub123.com): 用来探索数据，估计统计模型，进行统计测试
- [TensorFlow](https://www.tensorflow.org/tutorials/?from=www.mlhub123.com): TF官方文档
- [Theano](http://deeplearning.net/software/theano/?from=www.mlhub123.com): 允许高效地定义、优化以及评估涉及多维数组的数学表达式
- [openai](https://spinningup.openai.com/en/latest/?from=www.mlhub123.com): 强化学习
### C & C++
- [dlib](http://dlib.net?from=www.mlhub123.com): 实用的机器学习和数据分析工具包