ApacheCN 学习资源汇总 2019.3

本是古典何须时尚 2022-03-15 05:46 229阅读 0赞

# ApacheCN 学习资源 2019.3 #

*  【主页】 [apachecn.org][]
 *  【Github】[@ApacheCN][ApacheCN]
 *  暂时下线: 社区
 *  暂时下线: [cwiki 知识库][cwiki]
 *  自媒体平台
    
     *  [微博：@ApacheCN][ApacheCN 1]
     *  [知乎：@ApacheCN][ApacheCN 2]
     *  [CSDN][]
     *  [简书][Link 1]
     *  [OSChina][]
     *  [博客园][Link 2]
 *  **We are ApacheCN Open Source Organization, not ASF! We are fans of AI, and have no relationship with ASF!**
 *  合作or侵权，请联系【fonttian】[fonttian@gmail.com][fonttian_gmail.com] | 请抄送一份到 [apachecn@163.com][apachecn_163.com]

## 特色项目 ##

*  [PyTorch 0.2/0.3/0.4/1.0 中文文档和教程][PyTorch 0.2_0.3_0.4_1.0]
 *  [Sklearn 与 TensorFlow 机器学习实用指南][Sklearn _ TensorFlow]
 *  人工智能/机器学习/数据科学比赛系列
    
     *  [Kaggle 项目实战教程：文档 + 代码 + 视频][Kaggle _ _ _ _]
     *  [数据科学比赛收集平台][Link 3]
 *  [LeetCode，HackRank，剑指 offer，经典算法实现][LeetCode_HackRank_ offer]
 *  UCB CS/DS 系列课本
    
     *  [UCB CS61a 课本：SICP Python 描述][UCB CS61a _SICP Python]
     *  [UCB CS61b 课本：Java 中的数据结构][UCB CS61b _Java]
     *  [UCB Data8 课本：计算与推断思维][UCB Data8]
     *  [UCB Prob140 课本：面向数据科学的概率论][UCB Prob140]
     *  [UCB DS100 课本：数据科学的原理与技巧][UCB DS100]
 *  Numpy 技术栈中文文档
    
     *  [NumPy 中文文档][NumPy]
     *  [Pandas 中文文档][Pandas]
     *  [Matplotlib 中文文档][Matplotlib]
     *  [Sklearn 0.19 中文文档][Sklearn 0.19]
     *  [statsmodels 中文文档][statsmodels]

## Java 基础 ##

1.  [Java 编程思想][Java]
2.  [Java 从0～1个人笔记][Java _0_1]

## 大数据 ##

1.  [Spark 2.2.0 中文文档][Spark 2.2.0]
2.  [Storm 1.1.0 中文文档][Storm 1.1.0]
3.  [Kafka 1.0.0 中文文档][Kafka 1.0.0]
4.  [Beam 中文文档][Beam]
5.  [Zeppelin 0.7.2 中文文档][Zeppelin 0.7.2]
6.  [Elasticsearch 5.4 中文文档][Elasticsearch 5.4]
7.  [Kibana 5.2 中文文档][Kibana 5.2]
8.  [Kudu 1.4.0 中文文档][Kudu 1.4.0]
9.  [Spring Boot 1.5.2 中文文档][Spring Boot 1.5.2]
10. [Airflow 中文文档][Airflow]
11. [HBase 3.0 中文参考指南][HBase 3.0]
12. [Flink 1.7 中文文档][Flink 1.7]

## 区块链 ##

1.  [Solidity 中文文档][Solidity]

## 数学笔记 ##

1.  [MIT 18.06 线性代数笔记][MIT 18.06]

## Python 数据科学 ##

1.  [NumPy 中文文档][NumPy]
2.  [Pandas 中文文档][Pandas]
3.  [Matplotlib 中文文档][Matplotlib]
4.  [UCB Data8 课本：计算与推断思维][UCB Data8]
5.  [UCB Prob140 课本：面向数据科学的概率论][UCB Prob140]
6.  [UCB DS100 课本：数据科学的原理与技巧][UCB DS100]
7.  [利用 Python 进行数据分析 · 第 2 版][Python _ _ _ 2]
8.  [fast.ai 数值线性代数讲义 v2][fast.ai _ v2]
9.  [Pandas Cookbook 带注释源码][Pandas Cookbook]
10. [statsmodels 中文文档][statsmodels]
11. [数据科学 IPython 笔记本][IPython]

## CS 教程 ##

1.  [LeetCode，HackRank，剑指 offer，经典算法实现][LeetCode_HackRank_ offer]
2.  [GeeksForGeeks 翻译计划][GeeksForGeeks]
3.  [UCB CS61a 课本：SICP Python 描述][UCB CS61a _SICP Python]
4.  [UCB CS61b 课本：Java 中的数据结构][UCB CS61b _Java]
5.  [数据结构思维][Link 4]
6.  [中国大学 MOOC 计算机操作系统笔记][MOOC]
7.  [简单数据结构实现][Link 5]

## AI 教程 ##

1.  [AILearning - 机器学习实战][AILearning -]
2.  [Sklearn 与 TensorFlow 机器学习实用指南][Sklearn _ TensorFlow]
3.  [面向机器学习的特征工程][Link 6]
4.  [Python 数据分析与挖掘实战（带注释源码）][Python]
5.  [SciPyCon 2018 Sklearn 教程][SciPyCon 2018 Sklearn]
6.  [TensorFlow 学习指南][TensorFlow]
7.  [fast.ai 机器学习和深度学习中文笔记][fast.ai]
8.  [HackCV 网站文章翻译][HackCV]
9.  [台湾大学林轩田机器学习笔记][Link 7]
10. [Scikit-learn 秘籍][Scikit-learn]
11. [写给人类的机器学习][Link 8]
12. [数据科学和人工智能技术笔记][Link 9]

## AI 文档 ##

1.  [Sklearn 0.19 中文文档][Sklearn 0.19]
2.  [PyTorch 0.2/0.3/0.4/1.0 中文文档和教程][PyTorch 0.2_0.3_0.4_1.0]
3.  [XGBoost 中文文档][XGBoost]
4.  [LightGBM 中文文档][LightGBM]
5.  [FastText 中文文档][FastText]
6.  [Gensim 中文文档][Gensim]
7.  [OpenCV 4.0 中文文档][OpenCV 4.0]

## AI 比赛 ##

1.  [Kaggle 项目实战教程：文档 + 代码 + 视频][Kaggle _ _ _ _]
2.  [数据科学比赛收集平台][Link 3]

## 其它 ##

1.  [独立开发/自由职业/远程工作资源列表][Link 10]
2.  [通往财富自由之路精细笔记][Link 11]
3.  [5 分钟商学院精细笔记][5]

## 翻译征集 ##

要求：

*  机器学习/数据科学相关
 *  或者编程相关
 *  原文必须在互联网上开放
 *  不能只提供 PDF 格式（我们实在不想把精力都花在排版上）
 *  **请先搜索有没有人翻译过**

[请回复本文。][Link 12]

## 赞助我们 ##

![donate.jpg][]

[apachecn.org]: http://www.apachecn.org
[ApacheCN]: https://github.com/apachecn
[cwiki]: http://cwiki.apachecn.org
[ApacheCN 1]: https://weibo.com/u/6326715527
[ApacheCN 2]: https://www.zhihu.com/people/apachecn
[CSDN]: https://blog.csdn.net/wizardforcel/article/category/8437073
[Link 1]: https://www.jianshu.com/c/4ee721d0c474
[OSChina]: https://my.oschina.net/repine/
[Link 2]: https://www.cnblogs.com/wizardforcel/category/1352397.html
[fonttian_gmail.com]: mailto:fonttian@gmail.com
[apachecn_163.com]: mailto:apachecn@163.com
[PyTorch 0.2_0.3_0.4_1.0]: https://github.com/apachecn/pytorch-doc-zh
[Sklearn _ TensorFlow]: https://github.com/apachecn/hands-on-ml-zh
[Kaggle _ _ _ _]: https://github.com/apachecn/kaggle
[Link 3]: https://github.com/iphysresearch/DataSciComp
[LeetCode_HackRank_ offer]: https://github.com/apachecn/LeetCode
[UCB CS61a _SICP Python]: https://github.com/apachecn/sicp-py-zh
[UCB CS61b _Java]: https://github.com/apachecn/cs61b-textbook-zh
[UCB Data8]: https://github.com/apachecn/data8-textbook-zh
[UCB Prob140]: https://github.com/apachecn/prob140-textbook-zh
[UCB DS100]: https://github.com/apachecn/ds100-textbook-zh
[NumPy]: https://github.com/apachecn/numpy-ref-zh
[Pandas]: https://github.com/apachecn/pandas-doc-zh
[Matplotlib]: https://github.com/apachecn/matplotlib-user-guide-zh
[Sklearn 0.19]: https://github.com/apachecn/scikit-learn-doc-zh
[statsmodels]: https://github.com/apachecn/statsmodels_doc_zh
[Java]: https://github.com/apachecn/thinking-in-java-zh
[Java _0_1]: https://javaee.strivebo.com
[Spark 2.2.0]: https://github.com/apachecn/spark-doc-zh
[Storm 1.1.0]: https://github.com/apachecn/storm-doc-zh
[Kafka 1.0.0]: https://github.com/apachecn/kafka-doc-zh
[Beam]: https://github.com/apachecn/beam-site-zh
[Zeppelin 0.7.2]: https://github.com/apachecn/zeppelin-doc-zh
[Elasticsearch 5.4]: https://github.com/apachecn/elasticsearch-doc-zh
[Kibana 5.2]: https://github.com/apachecn/kibana-doc-zh
[Kudu 1.4.0]: https://github.com/apachecn/kudu-doc-zh
[Spring Boot 1.5.2]: https://github.com/apachecn/spring-boot-doc-zh
[Airflow]: https://github.com/apachecn/airflow-doc-zh
[HBase 3.0]: https://github.com/apachecn/hbase-doc-zh
[Flink 1.7]: https://github.com/apachecn/flink-doc-zh
[Solidity]: https://github.com/apachecn/solidity-doc-zh
[MIT 18.06]: https://github.com/apachecn/math
[Python _ _ _ 2]: https://github.com/apachecn/pyda-2e-zh
[fast.ai _ v2]: https://github.com/apachecn/fastai-num-linalg-v2-zh
[Pandas Cookbook]: https://github.com/apachecn/pandas-cookbook-code-notes
[IPython]: https://github.com/apachecn/ds-ipynb-zh
[GeeksForGeeks]: https://github.com/apachecn/geeksforgeeks-zh
[Link 4]: https://github.com/apachecn/think-dast-zh
[MOOC]: https://github.com/apachecn/Computer-operating-system-notes
[Link 5]: https://github.com/apachecn/DataStructure
[AILearning -]: https://github.com/apachecn/AiLearning
[Link 6]: https://github.com/apachecn/feature-engineering-for-ml-zh
[Python]: https://github.com/apachecn/python_data_analysis_and_mining_action
[SciPyCon 2018 Sklearn]: https://github.com/apachecn/scipycon-2018-sklearn-tut-zh
[TensorFlow]: https://github.com/apachecn/learning-tf-zh
[fast.ai]: https://github.com/apachecn/fastai-ml-dl-notes-zh
[HackCV]: https://github.com/apachecn/HackCV-Translate
[Link 7]: https://github.com/apachecn/ntu-hsuantienlin-ml
[Scikit-learn]: https://github.com/apachecn/sklearn-cookbook-zh
[Link 8]: https://github.com/apachecn/ml-for-humans-zh
[Link 9]: https://github.com/apachecn/ds-ai-tech-notes
[XGBoost]: https://github.com/apachecn/xgboost-doc-zh
[LightGBM]: https://github.com/apachecn/lightgbm-doc-zh
[FastText]: https://github.com/apachecn/fasttext-doc-zh
[Gensim]: https://github.com/apachecn/gensim-doc-zh
[OpenCV 4.0]: https://github.com/apachecn/opencv-doc-zh
[Link 10]: https://github.com/apachecn/awesome-indie-zh
[Link 11]: https://github.com/apachecn/the-way-to-wealth-freedom-notes
[5]: https://github.com/apachecn/5min-business-notes
[Link 12]: https://www.apachecn.org/translate/
[donate.jpg]: /images/20220315/ac130bfc9d9a4bfaba5ed4cd8522d72e.png