Applied machine learning

Forecasting, classification, scoring, optimisation, and decision support where specific models outperform generic tooling.

Use-case framing around the decision or operation to improve.
Model design, training, and evaluation tied to real data.
Readable performance evidence for business and technical teams.
Deployment planning for the systems that consume the model.