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Foundational Python for Data Science - Kennedy Behrman - Bog

Bag om Foundational Python for Data Science

Data science and machine learningtwo of the world's hottest fieldsare attracting talent from a wide variety of technical, business, and liberal arts disciplines. Python, the world's #1 programming language, is also the most popular language for data science and machine learning. This is the first guide specifically designed to help students with widely diverse backgrounds learn foundational Python so they can use it for data science and machine learning. This book is catered to introductory-level college courses on data science. Leading data science instructor and practitioner Kennedy Behrman first walks through the process of learning to code for the first time with Python and Jupyter notebook, then introduces key libraries every Python data science programmer needs to master. Once students have learned these foundations, Behrman introduces intermediate and applied Python techniques for real-world problem-solving. Throughout, Foundational Python for Data Science presents hands-on exercises, learning assessments, case studies, and moreall created with Colab (Jupyter compatible) notebooks, so students can execute all coding examples interactively without installing or configuring any software.

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  • Sprog:
  • Ukendt
  • ISBN:
  • 9780136624356
  • Indbinding:
  • Paperback
  • Sideantal:
  • 256
  • Udgivet:
  • 24. januar 2022
  • Størrelse:
  • 231x17x178 mm.
  • Vægt:
  • 446 g.
  • 4-7 hverdage.
  • 5. december 2024
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Beskrivelse af Foundational Python for Data Science

Data science and machine learningtwo of the world's hottest fieldsare attracting talent from a wide variety of technical, business, and liberal arts disciplines. Python, the world's #1 programming language, is also the most popular language for data science and machine learning. This is the first guide specifically designed to help students with widely diverse backgrounds learn foundational Python so they can use it for data science and machine learning. This book is catered to introductory-level college courses on data science. Leading data science instructor and practitioner Kennedy Behrman first walks through the process of learning to code for the first time with Python and Jupyter notebook, then introduces key libraries every Python data science programmer needs to master. Once students have learned these foundations, Behrman introduces intermediate and applied Python techniques for real-world problem-solving. Throughout, Foundational Python for Data Science presents hands-on exercises, learning assessments, case studies, and moreall created with Colab (Jupyter compatible) notebooks, so students can execute all coding examples interactively without installing or configuring any software.

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