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Data Science Fundamentals Pocket Primer
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Oswald Campesato
Language:
English
Published/Copyright:
2021
About this book
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
Author / Editor information
Campesato Oswald :
Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, TensorFlow, and NLP. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the NLP Using R Pocket Primer (all Mercury Learning and Information).
Supplementary Materials
Topics
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Publishing information
Pages and Images/Illustrations in book
eBook published on:
May 26, 2021
eBook ISBN:
9781683927327
Paperback published on:
June 8, 2021
Paperback ISBN:
9781683927334
Pages and Images/Illustrations in book
Main content:
428
Keywords for this book
Computer Science; Data Analytics; Programming; Python; NumPy; R; SQL; NoSQL; Pandas
Safety & product resources
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Manufacturer information:
Walter de Gruyter GmbH
Genthiner Straße 13
10785 Berlin
productsafety@degruyterbrill.com
