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Close 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 algebraProvides a thorough introduction to data visualization and regular expressionsCovers NumPy, Pandas, R, and SQLIntroduces probability and statistical conceptsFeatures numerous code samples throughoutCompanion files with source code and figuresThe companion files are available online by emailing the publisher with proof of purchase at info@merclearning.com.

Data Science Fundamentals Pocket Primer

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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, da

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Auteur(s): Campesato, Oswald

Editeur: Mercury Learning and Information

Collection: Pocket Primer

Année de Publication: 2021

pages: 450

Langue: Anglais

ISBN: 978-1-68392-733-4

eISBN: 978-1-68392-732-7

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, da

Voir toute la description...

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