Python for Probability, Statistics, and Machine Learning

Authors: Unpingco, José

  • 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
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eBook $109.00
price for USA (gross)
  • ISBN 978-3-319-30717-6
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $139.99
price for USA
  • ISBN 978-3-319-30715-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

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 mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples.  This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python programming.

About the authors

Dr. José Unpingco completed his PhD from the University of California, San Diego in 1998 and has since worked in industry as an engineer, consultant, and instructor on a wide-variety of advanced data processing and analysis topics, with deep experience in multiple machine learning technologies. He was the onsite technical director for large-scale Signal and Image Processing for the Department of Defense (DoD) where he also spearheaded the DoD-wide adoption of scientific Python. As the primary scientific Python instructor for the DoD, he has taught Python to over 600 scientists and engineers. Dr. Unpingco is currently the Technical Director for Data Science for a non-profit Medical Research Organization in San Diego, California.

Table of contents (4 chapters)

Buy this book

eBook $109.00
price for USA (gross)
  • ISBN 978-3-319-30717-6
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $139.99
price for USA
  • ISBN 978-3-319-30715-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Python for Probability, Statistics, and Machine Learning
Authors
Copyright
2016
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-30717-6
DOI
10.1007/978-3-319-30717-6
Hardcover ISBN
978-3-319-30715-2
Edition Number
1
Number of Pages
XV, 276
Number of Illustrations and Tables
103 b/w illustrations, 7 illustrations in colour
Topics