Python Data Science Handbook – Jake VanderPlas [英文] （PDF 高清扫描版 带完整目录标签）｜上口英语电子书资源分享

豆瓣评分9.3，从计算环境配置到机器学习实战书籍 大量示例 逐步讲解 举一反三 掌握用Scikit-Learn NumPy等工具高效存储 处理和分析数据 切实解决工作痛点

Python Data Science Handbook

作者: Jake VanderPlas
出版社: O’Reilly Media
副标题: Tools and Techniques for Developers
出版年: 2016-6-25 

《Python数据科学手册》是对以数据深度需求为中心的科学、研究以及针对计算和统计方法的参考书。

《Python数据科学手册》适合有编程背景，并打算将开源Python工具用作分析、操作、可视化以及学习数据的数据科学研究人员。 

内容简介

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.

Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.

With this handbook, you’ll learn how to use:

• IPython and Jupyter: provide computational environments for data scientists using Python
• NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python
• Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python
• Matplotlib: includes capabilities for a flexible range of data visualizations in Python
• Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

作者简介

Jake VanderPlas，Python科学栈深度用户和开发者，尤其擅长Python科学计算和数据可视化，是altair等可视化程序库的创建人，并为Scikit-Learn、IPython等Python程序库做了大量贡献。现任美国华盛顿大学eScience学院物理科学研究院院长。

电子书信息

文件类型：电子书 E-book 包括(pdf (扫描版))

下载方式：网盘下载

语言(Language)：简体中文(Chinese)

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