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Data Science

- A First Introduction with Python
Af: Trevor Campbell, Joel Ostblom, Tiffany Timbers, Melissa Lee, Lindsey Heagy Engelsk Paperback

Data Science

- A First Introduction with Python
Af: Trevor Campbell, Joel Ostblom, Tiffany Timbers, Melissa Lee, Lindsey Heagy Engelsk Paperback
Tjek vores konkurrenters priser

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.
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Tjek vores konkurrenters priser
Normalpris
kr 611
Fragt: 39 kr
6 - 8 hverdage
20 kr
Pakkegebyr
God 4 anmeldelser på
Tjek vores konkurrenters priser

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.
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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 432
ISBN-13: 9781032572239
Indbinding: Paperback
Udgave:
ISBN-10: 103257223X
Kategori: Programmering / softwareudvikling
Udg. Dato: 23 aug 2024
Længde: 29mm
Bredde: 177mm
Højde: 253mm
Forlag: Taylor & Francis Ltd
Oplagsdato: 23 aug 2024
Forfatter(e): Trevor Campbell, Joel Ostblom, Tiffany Timbers, Melissa Lee, Lindsey Heagy
Forfatter(e) Trevor Campbell, Joel Ostblom, Tiffany Timbers, Melissa Lee, Lindsey Heagy

Kategori Programmering / softwareudvikling

ISBN-13 9781032572239

Sprog Engelsk

Indbinding Paperback

Sider 432

Udgave

Længde 29mm

Bredde 177mm

Højde 253mm

Udg. Dato 23 aug 2024

Oplagsdato 23 aug 2024

Forlag Taylor & Francis Ltd

Kategori sammenhænge