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 Includes companion files with source code and figures
Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the Python Pocket Primer (Mercury Learning).
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.