

Practical machine learning, forecasting and AI evaluation
I help product teams decide whether a model is useful for their actual workflow. That might mean an evaluation set for a support assistant or a forecast with honest error bounds. You receive reproducible notebooks, documented assumptions and a results walkthrough, including the cases where the approach does not work well.



We had a tight launch window. The work on benchmark report was ready for our team to review on schedule.
Service: I will evaluate your AI assistant against real support questions
We had a tight launch window. The work on forecast model was ready for our team to review on schedule.
Service: I will build a sales forecasting model from your historical data
The benchmark report matched our references closely, and the final files were organised well.
Service: I will evaluate your AI assistant against real support questions
We had a tight launch window. The work on benchmark report was ready for our team to review on schedule.
Service: I will evaluate your AI assistant against real support questions
The evaluation dataset matched our references closely, and the final files were organised well.
Service: I will evaluate your AI assistant against real support questions
Seller's reply
Thanks! Glad the team picked it up so quickly, that's always the best sign.
Our brief was understood from the first draft. The validation report made the whole project worthwhile.
Service: I will build a sales forecasting model from your historical data
Seller's reply
Appreciate it. Happy to help with the next stage whenever you're ready.