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Introduction to Computation and Programming Using Python, third edition
Introduction to Computation and Programming Using Python, third edition
Knygos.lt klubas Knygos.lt nariams
93,09 €
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132,99 €
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The new edition of an introduction to the art of computational problem solving using Python.This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including numpy, matplotlib, random, pandas, and sklearn. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computati…
  • Leidėjas:
  • Metai: 2021
  • Puslapiai: 496
  • ISBN-10: 0262542366
  • ISBN-13: 9780262542364
  • Formatas: 17.6 x 22.6 x 3.1 cm, minkšti viršeliai
  • Kalba: Anglų

Introduction to Computation and Programming Using Python, third edition (el. knyga) (skaityta knyga) | knygos.lt

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The new edition of an introduction to the art of computational problem solving using Python.

This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including numpy, matplotlib, random, pandas, and sklearn. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data as well as substantial material on machine learning.

All of the code in the book and an errata sheet are available on the book's web page.
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  • Autorius: John V. Guttag
  • Leidėjas:
  • Metai: 2021
  • Puslapiai: 496
  • ISBN-10: 0262542366
  • ISBN-13: 9780262542364
  • Formatas: 17.6 x 22.6 x 3.1 cm, minkšti viršeliai
  • Kalba: Anglų

The new edition of an introduction to the art of computational problem solving using Python.

This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including numpy, matplotlib, random, pandas, and sklearn. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data as well as substantial material on machine learning.

All of the code in the book and an errata sheet are available on the book's web page.

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