Python Data Science (PDF)
Unlike conventional textbooks, it is based on Markdown and uses full-color...
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Rather than presenting Python as Java or C, this book focuses on the essential Python programming skills for data scientists and advanced methods for big data analysts.
Unlike conventional textbooks, it is based on Markdown and uses full-color printing and a code-centric approach to highlight the 3C principles in data science: creative design of data solutions, curiosity about the data lifecycle, and critical thinking regarding data insights. Q&A-based knowledge maps, tips and suggestions, notes, as well as warnings and cautions are employed to explain the key points, difficulties, and common mistakes in Python programming for data science. In addition, it includes suggestions for further reading.
This textbook provides an open-source community via GitHub, and the course materials are licensed for free use under the following license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).
He is the author of Data Science (Tsinghua University Press, 2016), the first monograph in China that systematically introduced data science principles, theories, methods, technologies, and tools. His textbook Data Science Theory and Practice (Second Edition) was recognized as a high-quality textbook by the Beijing Municipal Education Commission in 2019. His course Introduction to Data Science is one of the China National First-Class Undergraduate Courses.
- Autor: Chaolemen Borjigin
- 2023, 1st ed. 2023, 345 Seiten, Englisch
- Verlag: Springer Nature Singapore
- ISBN-10: 981197702X
- ISBN-13: 9789811977022
- Erscheinungsdatum: 30.06.2023
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 35 MB
- Ohne Kopierschutz
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