Python for Data Science For Dummies

Nonfiction, Computers, Programming
Cover of the book Python for Data Science For Dummies by John Paul Mueller, Luca Massaron, Wiley
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Author: John Paul Mueller, Luca Massaron ISBN: 9781119547662
Publisher: Wiley Publication: January 29, 2019
Imprint: For Dummies Language: English
Author: John Paul Mueller, Luca Massaron
ISBN: 9781119547662
Publisher: Wiley
Publication: January 29, 2019
Imprint: For Dummies
Language: English

The fast and easy way to learn Python programming and statistics

Python is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library.

Python For Data Science For Dummies is written for people who are new to data analysis, and discusses the basics of Python data analysis programming and statistics. The book also discusses Google Colab, which makes it possible to write Python code in the cloud.

  • Get started with data science and Python
  • Visualize information
  • Wrangle data
  • Learn from data

The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

The fast and easy way to learn Python programming and statistics

Python is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library.

Python For Data Science For Dummies is written for people who are new to data analysis, and discusses the basics of Python data analysis programming and statistics. The book also discusses Google Colab, which makes it possible to write Python code in the cloud.

The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.

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