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Data Science Fundamentals Pocket Primer

Data Science Fundamentals Pocket Primer
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Oswald Campesato
Mercury Learning and Information
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Artikel-Nr:
9781683927327
Veröffentl:
2021
Einband:
PDF
Seiten:
428
Autor:
Oswald Campesato
Serie:
Pocket Primer
eBook Typ:
PDF
eBook Format:
PDF
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Deutsch
Systemvoraussetzungen
Beschreibung:

As part of the best-sellingPocket Primer series, this book is designed to introduce the reader to the basic concepts of data science using Python 3 and other computer applications. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, linear algebra, and regular expressions. The book includes numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available.

FEATURES:
  • Includes a concise introduction to Python 3 and linear algebra
  • Provides a thorough introduction to data visualization and regular expressions
  • Covers NumPy, Pandas, R, and SQL
  • Introduces probability and statistical concepts
  • Features numerous code samples throughout
  • Companion files with source code and figures
The companion files are available online by emailing the publisher with proof of purchase at info@merclearning.com.
As part of the best-sellingPocket Primer series, this book is designed to introduce the reader to the basic concepts of data science using Python 3 and other computer applications. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, linear algebra, and regular expressions. The book includes numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available.

FEATURES:
  • Includes a concise introduction to Python 3 and linear algebra
  • Provides a thorough introduction to data visualization and regular expressions
  • Covers NumPy, Pandas, R, and SQL
  • Introduces probability and statistical concepts
  • Features numerous code samples throughout
  • Companion files with source code and figures
The companion files are available online by emailing the publisher with proof of purchase at info@merclearning.com.

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