ApacheCN 数据科学译文集 20210313 更新
新增了五个教程：
Python 和 Jupyter 机器学习入门：github.com/apachecn/apachecn-ds-zh/blob/master/docs/begin-ds-py-jupyter/README.md
零、前言：github.com/apachecn/apachecn-ds-zh/blob/master/docs/begin-ds-py-jupyter/0.md
一、Jupyter 基础知识：github.com/apachecn/apachecn-ds-zh/blob/master/docs/begin-ds-py-jupyter/1.md
二、数据清理和高级机器学习：github.com/apachecn/apachecn-ds-zh/blob/master/docs/begin-ds-py-jupyter/2.md
三、Web 爬取和交互式可视化：github.com/apachecn/apachecn-ds-zh/blob/master/docs/begin-ds-py-jupyter/3.md
Python 数据科学和机器学习实践指南：github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-ds-py-ml/README.md
零、前言：github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-ds-py-ml/00.md
一、入门：github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-ds-py-ml/01.md
二、统计和概率回顾和 Python 实践：github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-ds-py-ml/02.md
三、Matplotlib 和高级概率概念：github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-ds-py-ml/03.md
四、预测模型：github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-ds-py-ml/04.md
五、Python 机器学习：github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-ds-py-ml/05.md
六、推荐系统：github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-ds-py-ml/06.md
七、更多数据挖掘和机器学习技术：github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-ds-py-ml/07.md
八、处理真实数据：github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-ds-py-ml/08.md
九、Apache Spark-大数据机器学习：github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-ds-py-ml/09.md
十、测试与实验设计：github.com/apachecn/apachecn-ds-zh/blob/master/docs/handson-ds-py-ml/10.md
精通 Python 数据科学：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/README.md
零、前言：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/00.md
一、原始数据入门：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/01.md
二、推断统计：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/02.md
三、大海捞针：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/03.md
四、通过高级可视化感知数据：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/04.md
五、发现机器学习：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/05.md
六、使用线性回归执行预测：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/06.md
七、估计事件的可能性：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/07.md
八、使用协同过滤生成建议：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/08.md
九、使用集成模型扩展边界：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/09.md
十、通过 K 均值聚类应用细分：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/10.md
十一、通过文本挖掘分析非结构化数据：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/11.md
十二、在大数据世界中利用 Python：github.com/apachecn/apachecn-ds-zh/blob/master/docs/master-py-ds/12.md
Python 数据科学本质论：github.com/apachecn/apachecn-ds-zh/blob/master/docs/py-ds-essentials/README.md
零、前言：github.com/apachecn/apachecn-ds-zh/blob/master/docs/py-ds-essentials/0.md
一、第一步：github.com/apachecn/apachecn-ds-zh/blob/master/docs/py-ds-essentials/1.md
二、数据整理：github.com/apachecn/apachecn-ds-zh/blob/master/docs/py-ds-essentials/2.md
三、数据管道：github.com/apachecn/apachecn-ds-zh/blob/master/docs/py-ds-essentials/3.md
四、机器学习：github.com/apachecn/apachecn-ds-zh/blob/master/docs/py-ds-essentials/4.md
五、可视化，见解和结果：github.com/apachecn/apachecn-ds-zh/blob/master/docs/py-ds-essentials/5.md
六、社交网络分析：github.com/apachecn/apachecn-ds-zh/blob/master/docs/py-ds-essentials/6.md
七、超越基础的深度学习：github.com/apachecn/apachecn-ds-zh/blob/master/docs/py-ds-essentials/7.md
八、大数据和 Spark：github.com/apachecn/apachecn-ds-zh/blob/master/docs/py-ds-essentials/8.md
九、加强您的 Python 基础：github.com/apachecn/apachecn-ds-zh/blob/master/docs/py-ds-essentials/9.md
数据科学思想：github.com/apachecn/apachecn-ds-zh/blob/master/docs/thoughtful-ds/README.md
零、前言：github.com/apachecn/apachecn-ds-zh/blob/master/docs/thoughtful-ds/00.md
一、开发人员对数据科学的看法：github.com/apachecn/apachecn-ds-zh/blob/master/docs/thoughtful-ds/01.md
二、使用 Jupyter 笔记本和 PixieDust 的大规模数据科学：github.com/apachecn/apachecn-ds-zh/blob/master/docs/thoughtful-ds/02.md
三、PixieApp 深入了解：github.com/apachecn/apachecn-ds-zh/blob/master/docs/thoughtful-ds/03.md
四、使用 PixieGateway 服务器将 PixieApp 部署到 Web：github.com/apachecn/apachecn-ds-zh/blob/master/docs/thoughtful-ds/04.md
五、最佳实践和高级 PixieDust 概念：github.com/apachecn/apachecn-ds-zh/blob/master/docs/thoughtful-ds/05.md
六、TensorFlow 图像识别：github.com/apachecn/apachecn-ds-zh/blob/master/docs/thoughtful-ds/06.md
七、大数据和 Twitter 情感分析：github.com/apachecn/apachecn-ds-zh/blob/master/docs/thoughtful-ds/07.md
八、金融时间序列分析和预测：github.com/apachecn/apachecn-ds-zh/blob/master/docs/thoughtful-ds/08.md
九、使用图的美国国内航班数据分析：github.com/apachecn/apachecn-ds-zh/blob/master/docs/thoughtful-ds/09.md
十、最终思想：github.com/apachecn/apachecn-ds-zh/blob/master/docs/thoughtful-ds/10.md
十一、附录 A：PixieApp 快速参考：github.com/apachecn/apachecn-ds-zh/blob/master/docs/thoughtful-ds/11.md
下载
Docker
docker pull apachecn0/apachecn-cv-zh
docker run -tid -p <port>:80 apachecn0/apachecn-cv-zh
# 访问 http://localhost:{port}
PYPI
pip install apachecn-cv-zh
apachecn-cv-zh <port>
# 访问 http://localhost:{port}
NPM
npm install -g apachecn-cv-zh
apachecn-cv-zh <port>
# 访问 http://localhost:{port}
贡献指南
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