Data Science Fundamentals Pocket Primer - Softcover

Campesato, Oswald

 
9781683927334: Data Science Fundamentals Pocket Primer

Inhaltsangabe

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.

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Über die Autorin bzw. den Autor

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

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