

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 data cleaning was ready for our team to review on schedule.
Service: I will build a sales forecasting model from your historical data
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
Really pleased with the data cleaning. We could put the delivery to use without another meeting.
Service: I will build a sales forecasting model from your historical data
The evaluation dataset fit our brief. I would leave more time for the final review on our next project.
Service: I will evaluate your AI assistant against real support questions
Seller's reply
Thanks, it was a pleasure. Still around if anything comes up.
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
Our team is happy with the error analysis. The explanation at handover was especially helpful.
Service: I will evaluate your AI assistant against real support questions