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Python data science

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Python data scienceby Chaolemen Borjigin.
作者:	Borjigin, Chaolemen.
出版者:	Singapore :Springer Nature Singapore :2023.
面頁冊數:	xii, 345 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Python (Computer program language)
電子資源:	https://doi.org/10.1007/978-981-19-7702-2
ISBN:	9789811977022$q(electronic bk.)

Python data science
Borjigin, Chaolemen.

Python data science[electronic resource] /by Chaolemen Borjigin. - Singapore :Springer Nature Singapore :2023. - xii, 345 p. :ill. (some col.), digital ;24 cm.

1. Python and Data Science -- 2. Basic Python Programming for Data Science -- 3. Advanced Python Programming for Data Science -- 4. Data preprocessing and wrangling -- 5. Data analysis algorithms and models.

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)

ISBN: 9789811977022$q(electronic bk.)

Standard No.: 10.1007/978-981-19-7702-2doiSubjects--Topical Terms:

215247
Python (Computer program language)

LC Class. No.: QA76.73.P98 / B67 2023

Dewey Class. No.: 005.133

Python data science
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245 1 0 $a Python data science $h [electronic resource] / $c by Chaolemen Borjigin.
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300 $a xii, 345 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a 1. Python and Data Science -- 2. Basic Python Programming for Data Science -- 3. Advanced Python Programming for Data Science -- 4. Data preprocessing and wrangling -- 5. Data analysis algorithms and models.
520 $a 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)
650 0 $a Python (Computer program language) $3 215247
650 0 $a Big data. $3 609582
650 0 $a Data mining. $3 184440
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856 4 0 $u https://doi.org/10.1007/978-981-19-7702-2
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