Description
PyData DC 2016
Logistic Regression models are powerful tools in the data science toolkit; in this talk we will explore various implementations of logistic regression in Python and SAS, with a focus on output and performance. We will also discuss both the numerical and statistical implications (including Bayesian interpretations) of the various options.