Getting started with linear regression

This post introduces logistic regression as a binary classification algorithm, detailing its implementation in Python using scikit-learn. It covers data loading, preprocessing (including handling categorical features with one-hot encoding and binary encoding), determining a baseline accuracy, training the model, and evaluating its performance using a confusion matrix, precision, recall, and accuracy metrics. The post also touches upon interpreting the results and briefly discusses data imbalance.