resemble is an R package for similarity-based modelling and local learning in spectroscopy. It provides tools for dissimilarity computation, nearest-neighbour search, memory-based learning, and spectral library optimisation (methods designed for large, heterogeneous spectral datasets where global models underperform)

Source code for 'Lemna: Explaining deep learning based security applications'.

Wind Power Prediction with ECMWF Data as Input using Statistical Learning

Comparative analysis of nonparametric regression methods (KNN, LOWESS, Bin, Kernel, Local Linear) to explore the nonlinear relationship between health expenditure and life expectancy using WHO data (2000–2015).

Implementation of LOWESS (Locally Weighted Scatterplot Smoothing) algorithm with bootstrap confidence intervals for nonparametric regression and data smoothing in Python.

A library of smoothing kernels in multiple languages for use in kernel regression and kernel density estimation.