Chaolemen Borjigin - Böcker
Visar alla böcker från författaren Chaolemen Borjigin. Handla med fri frakt och snabb leverans.
4 produkter
4 produkter
Del 12999 - Lecture Notes in Computer Science
Web Information Systems and Applications
18th International Conference, WISA 2021, Kaifeng, China, September 24–26, 2021, Proceedings
Häftad, Engelska, 2021
1 205 kr
Skickas inom 10-15 vardagar
This book constitutes the proceedings of the 18th International Conference on Web Information Systems and Applications, WISA 2021, held in Kaifeng, China, in September 2021.
878 kr
Skickas inom 10-15 vardagar
Rather than presenting Python as Java or C, this textbook 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).More teaching materials including Codes, Datasets, Slides, Syllabus can be found at https://github.com/LemenChao/PythonDataScience
653 kr
Skickas inom 5-8 vardagar
660 kr
Skickas inom 10-15 vardagar
Rather than presenting Python as Java or C, this textbook 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).More teaching materials including Codes, Datasets, Slides, Syllabus can be found at https://github.com/LemenChao/PythonDataScience