Cost-aware credit card fraud detection pipeline: time-based split, probability calibration, and business-aligned threshold tuning (AUPRC-first).

A time slicer for training and testing temporally correlated Machine Learning models.

Predict NYC restaurant inspection grades (A vs B/C+) with leak-safe, time-split ML baselines.

Practical guide to validating time-series models: stationary vs non-stationary setups, leakage pitfalls, expanding/rolling TimeSeriesSplit, Ridge/LinearRegression baselines, and bootstrap CIs for metrics. Includes utilities for feature engineering (percent_change) and visualization.

Predicting House Prices — End-to-End Regression Workflow