Artificial Intelligence and Machine Learning
We apply classification, regression, clustering and pattern models to your data and deliver the results as a scientific report.
What we do
We build machine learning models for your data set and — just as importantly — we say what those models can and cannot tell you.
- Classification and regression — from logistic regression through to ensemble methods.
- Clustering and pattern discovery — structures that are not labelled in advance.
- Model validation — cross-validation, overfitting checks, and honest reporting of performance on unseen data.
- Interpretability — which variables drive the result, and how strongly.
What we do not do
We do not present a model whose performance we cannot defend. If the data set is too small or too imbalanced for the question being asked, we say so before the work starts rather than after.
What you receive
A scientific report: the modelling choices, the validation strategy, the measured performance, and the limits of what the model supports.