Data Science Fundamentals Pocket Primer

Oswald Campesato

$59.95

Publication Date: May 25th, 2021

Publisher:

Mercury Learning and Information

ISBN:

9781683927334

Pages:

428

Special Order - Subject to Availability

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.

About the Author

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).