数据科学初探：以Python为例（True EPUB）
Data Science: A First Introduction with Python focuses on using the Python programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, regression, clustering, and inference. It emphasizes workflows that are clear, reproducible, and shareable, and includes coverage of the basics of version control. Based on educational research and active learning principles, the book uses a modern approach to Python and includes accompanying autograded Jupyter worksheets for interactive, self-directed learning. The text will leave readers well-prepared for data science projects. It is designed for learners from all disciplines with minimal prior knowledge of mathematics and programming. The authors have honed the material through years of experience teaching thousands of undergraduates at the University of British Columbia.
Key Features Includes autograded worksheets for interactive, self-directed learning. Introduces readers to modern data analysis and workflow tools such as Jupyter notebooks and GitHub, and covers cutting-edge data analysis and manipulation Python libraries such as pandas, scikit-learn, and altair. Is designed for a broad audience of learners from all backgrounds and disciplines.
英文| 2024 |国际标准图书编号：9781003438397 | 732页|真正的EPUB | 16.95 MB 数据科学：Python入门侧重于在Jupyter笔记本中使用Python编程语言进行数据操作和清理，创建有效的可视化，并使用分类、回归、聚类和推理从数据中提取见解。它强调清晰、可复制和可共享的工作流程，并涵盖了版本控制的基础知识。基于教育研究和主动学习原则，这本书使用了一种现代的Python方法，并附带了用于交互式自主学习的亲笔签名的Jupyter工作表。这篇文章将让读者为数据科学项目做好充分准备。它是为所有学科的学习者设计的，他们对数学和编程的先验知识最少。作者通过多年在不列颠哥伦比亚大学教授数千名本科生的经验磨练了这些材料。 主要功能包括用于交互式自主学习的亲笔签名工作表。向读者介绍现代数据分析和工作流工具，如Jupyter notebook和GitHub，并介绍尖端的数据分析和操作Python库，如pandas、scikit-learn和altair。专为来自不同背景和学科的广大学习者而设计。本站不对文件进行储存，仅提供文件链接，请自行下载，本站不对文件内容负责，请自行判断文件是否安全，如发现文件有侵权行为，请联系管理员删除。
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