Getting Started in Machine Learning: Easy Recipes for Python 3, Scikit-Learn, and Jupyter

by Isabella Romeo, Bruce Shapiro

Overview

This is an introductory book in machine learning with a hands on approach. It uses Python 3 and Jupyter notebooks for all applications. The emphasis is primarily on learning to use existing libraries such as Scikit-Learn with easy recipes and existing data files that can found on-line. Topics include linear, multilinear, polynomial, stepwise, lasso, ridge, and logistic regression; ROC curves and measures of binary classification; nonlinear regression (including an introduction to gradient descent); classification and regression trees; random forests;  neural networks; probabilistic methods (KNN, naive Bayes', QDA, LDA); dimensionality reduction with PCA; support vector machines; and clustering with K-Means, hierarchical, and DBScan. Appendices provide a review of probability and linear algebra. While some mathematical foundation is provided, it is not essential for understanding the implementations. The target audience is advanced community college students and intermediate university students in the sciences and engineering.  All code is available online.

Product Details

ISBN-13:	9780996686082
Publisher:	Sherwood Forest Books
Publication date:	12/09/2019
Pages:	346
Product dimensions:	7.00(w) x 10.00(h) x 0.81(d)

About the Author

Isabella Romeo is a pseudonym for Bruce E. Shapiro. Bella is a blue nose American Staffordshire Terrier. Romeo, a red nose pit, was her life partner and constant companion. Bella's hobbies include barking at trees, chasing grasshoppers, and sleeping on the living room couch. Since she does not have opposable thumbs, she dictated this book to her human, who, in turn, did all the typing for her. Not only does he have opposable thumbs, sometimes it seems like he has ten of them (for example, he totally ignores the little red lines under words -- what is this thing you call ``spell check?''). Said human with opposable thumbs and extraordinary typing skills has taught undergraduate mathematics at a California State University campus for the past two decades. In his alternate and sometime prior incarnations he was a senior researcher in the machine learning group at JPL, a computational scientist at Caltech, and a satellite orbital design and mission engineer under contract at the NASA/Goddard Space Flight Center.