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Data Science Fundamentals Pocket Primer de Oswald Campesato

Data Science Fundamentals Pocket Primer: Pocket Primer

Autor Oswald Campesato
en Limba Engleză Paperback – 8 iun 2021
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
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Specificații

ISBN-13: 9781683927334
ISBN-10: 1683927338
Pagini: 450
Dimensiuni: 152 x 229 x 25 mm
Greutate: 0.65 kg
Ediția:1. Auflage
Editura: Mercury Learning and Information
Colecția Pocket Primer
Seria Pocket Primer

Notă biografică

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).

Cuprins

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