Python for Probability, Statistics, and Machine Learning (Springer)
Monday, 22 July 2019

This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas.  Author Dr. José Unpingco develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes. Detailed proofs for certain important results are also provided.

Modern Python modules like Pandas, Sympy, Scikit-learn, Tensorflow, and Keras are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization.

Author: Dr. José Unpingco
Publisher: Springer
Date: June 2019
Pages: 384
ISBN: 978-3030185442
Print: 3030185443
Kindle: B07TQCV5VZ
Audience: Python developers with an undergraduate-level exposure to probability, statistics, or machine learning
Level: Intermediate/Advanced
Category: Artificial Intelligence

 

For recommendations of Python books see Books for Pythonistas and Python Books For Beginners in our Programmer's Bookshelf section.

For more Book Watch just click.

Book Watch is I Programmer's listing of new books and is compiled using publishers' publicity material. It is not to be read as a review where we provide an independent assessment. Some, but by no means all, of the books in Book Watch are eventually reviewed.

To have new titles included in Book Watch contact  BookWatch@i-programmer.info

Follow @bookwatchiprog on Twitter or subscribe to I Programmer's Books RSS feed for each day's new addition to Book Watch and for new reviews.

 

 

Banner
 


Visual Complex Analysis

Author:  Tristan Needham
Publisher: Clarendon Press
Pages: 616
ISBN: 978-0198534464
Print: 0198534469
Kindle: B0BNKJTJK1
Audience: The mathematically able and enthusiastic
Rating: 5
Reviewer: Mike James
What's complex about complex analysis?



Visual Differential Geometry and Forms

Author:  Tristan Needham
Publisher: Princeton
Pages: 584
ISBN: 978-0691203706
Print: 0691203709
Kindle: B08TT6QBZH
Audience: Math enthusiasts
Rating: 5
Reviewer: Mike James
The best math book I have read in a long time...


More Reviews