AI-Based Early Warning System for Delivery Failures

An AI-based early warning system for delivery failures.

An AI-based early warning system for delivery failures. As a reference project it shows how a system like this is put together in practice, which parts matter and how they are tested, so that a developer can learn from it and build on it.

It suits learners who want hands-on experience of the whole machine learning workflow: data collection and cleaning, feature engineering, model training and tuning, evaluation and presenting results.

The main parts are real-time processing of incoming data, alerts when a threshold or risk is reached, data preparation and exploration, model training and comparison of algorithms, and evaluation with standard metrics. The reference build uses Python, scikit-learn, Pandas, and Flask, with a clear project structure, setup instructions and sample data so that it can be run and extended.