Data Science Fundamentals Pocket Primer

by Oswald Campesato

Overview

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 [e-mail].

Product Details

ISBN-13:	9781683927334
Publisher:	Mercury Learning and Information
Publication date:	05/25/2021
Series:	Pocket Primer
Pages:	428
Product dimensions:	6.00(w) x 9.00(h) x (d)

About the Author

Oswald Campesato specializes in Deep Learning, Python, Data Science, and generative AI. He is the author/co-author of over forty-five books including Google Gemini for Python, Large Language Models, and GPT-4 for Developers (all Mercury Learning).

Table of Contents

1: Working with Data
2: Introduction to Probability and Statistics
3: Linear Algebra Concepts
4: Introduction to Python
5: Introduction to NumPy
6: Introduction to Pandas
7: Introduction to R
8: Regular Expressions
9: SQL and NoSQL
10: Data Visualization
Index