Testing out ClearML.

This project focuses on building an end-to-end time series forecasting system to predict daily grocery sales for different product families across multiple stores. The goal is to leverage historical sales data along with external factors such as promotions, holidays, and oil prices to accurately forecast future demand.

This project centers on the development of a predictive model aimed at optimizing order fulfillment processes by proactively identifying inventory items at risk of depletion.

This project involves predicting customer churn in a telecommunications company using machine learning techniques, exploring various features' impact, optimizing models, and identifying key factors influencing churn.