Data Science Fundamentals Pocket Primer / / Oswald Campesato.

• VerfasserIn: Campesato, Oswald,
• Place / Publishing House: Dulles, VA : : Mercury Learning and Information, , [2021]; ©2021
• Year of Publication: 2021
• Language: English
• Series: Pocket Primer
• Physical Description: 1 online resource (428 p.)
• Other title: Frontmatter --; Contents --; Preface --; Chapter 1. Working With Data --; Chapter 2. Intro to Probability and Statistics --; Chapter 3. Linear Algebra Concepts --; Chapter 4. Introduction to Python --; Chapter 5. Introduction to NumPy --; Chapter 6. Introduction to Pandas --; Chapter 7. Introduction to R --; Chapter 8. Regular Expressions --; Chapter 9. SQL and NoSQL --; Chapter 10. Data Visualization --; Index
• Format: Mode of access: Internet via World Wide Web.
• ISBN: 9781683927327
• Access: restricted access
• Hierarchical level: Monograph
• Statement of Responsibility: Oswald Campesato.

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 [e-mail].