The book is a showcase of logistic regression theory and application of statistical machine learning with Python.  Topics include logit, probit, and complimentary log-log models with a binary target as well as multinomial regression.  A section about contingency tables is also provided.   Scikit-Learn and statsmodels are the two Python packages used to illustrate how to tune parameters for better fit and accuracy.   For a quick view of the table of contents, click here.