Examples of some my published work can be found on Kaggle, where I maintain a selection of my notebooks, I am also author of "The Orange Book of Machine Learning". Previously I worked as an academic researcher in the field of statistical mechanics and thermodynamics, and a list of the over 40 publications that I have co-authored can be found on my home page (h-index=23).
My primary skills are
- Data exploration and experimentation
- Predictive modelling of tabular / structured data using the tools of machine learning
- Proof of concept (PoC) prototype models
- regression techniques with conformal prediction intervals, well calibrated classification
If you wish to get in touch it would be a pleasure to connect on LinkedIn.
Needless to say a great deal of what I do is facilitated by the work of others, and the vast majority of the source of the python packages can be found right here on GitHub, for example:
- scikit-learn
- NumPy / SciPy
- pandas / polars
- statsmodels
- XGBoost / CatBoost / LightGBM
- TabNet
- quantile-forest
- MAPIE
- keras
- cuML
- Matplotlib / plotly / seaborn
along with
All the best,
carl