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Data Science Fundamentals Pocket Primer Cover

Data Science Fundamentals Pocket Primer

Volume in the series
Pocket Primer
Publisher:Mercury Learning and Information
By: Oswald Campesato  
Paid access
|May 2021
Product purchase options
Print: Available at Amazon
Description
As part of the best-selling Pocket 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.
PDF ISBN: 978-1-68392-732-7 | E-Pub ISBN: 978-1-68392-731-0 | Paperback ISBN: 978-1-68392-733-4 | DOI: https://doi.org/10.1515/9781683927327
Publisher: Mercury Learning and Information
Copyright owner: © 2021 Walter de Gruyter GmbH, Berlin/Boston
Publication date: 2021
Language: English
Pages: 428
Keywords:
r,
nosql,
computer science,
pandas,
programming,
data analytics,
numpy,
python,
sql,
programming,
data
Related subjects:
Computer sciences,
Programming and languages,
Computer sciences, other

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