/retail_sales_time_series

A repo containing a few exploratory notebooks for statistical (ARIMA) and supervised ML (random forest, KNN) approaches to time series analysis of monthly retail sales (sourced from St. Louis Fed). Notebooks also explore the use of MLFlow for experiment tracking, model registration, and deployment/inference.

Primary LanguageJupyter Notebook

retail_sales_time_series

A repo containing a few exploratory notebooks for statistical (ARIMA) and supervised ML (random forest, KNN) approaches to time series analysis of monthly retail sales (sourced from St. Louis Fed). Notebooks also explore the use of MLFlow for experiment tracking, model registration, and deployment/inference.