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Python for Probability, Statistics, and Machine Learning by José Unpingco is a nonfiction available to read on EtoBox.

What is Python for Probability, Statistics, and Machine Learning about?

Springer, 2016. — 276 p. — ISBN: 3319307150 Explains how to simulate, conceptualize, and visualize random statistical processes and apply machine learning methods Connects to key open-source Python communities and corresponding modules focused on the latest developments in this area Outlines probability, statistics, and machine learning concepts using an intuitive visual approach, backed up with corresponding visualization codes This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mat

Who reads Python for Probability, Statistics, and Machine Learning?

Author

José Unpingco

Publisher

Springer International Publishing : Imprint: Springer

Published

2016

Language

EN

ISBN

9783319307152

Category

nonfiction

Subjects

Mathematics, Engineering, Computer Science

Updated

2026-03-24