Logistic Regression from the ground up
Logistic regression from first principles. Focus is on model formulation, log-odds interpretation, regularisation, gradient and Hessian derivations, and the multinomial case.
Blog
Technical notes about scientific computing, signal processing, machine learning, Python, and optimisation.
An introduction to Radial basis functions
How radial basis function (RBF) surrogate models work, and how to implement a Gaussian RBF interpolation and regression model in Python with NumPy and SciPy.
Introduction to Latex With Assistance From Zotero
How to set up Zotero with Better BibTeX to keep one .bib file in sync for LaTeX referencing, plus TeXstudio settings and finding papers with Research Rabbit.
Time synchronous averaging and computed order tracking: Explained
Time synchronous averaging (TSA) and computed order tracking (COT) explained for vibration analysis, with step-by-step procedures and toy-signal examples.
The Fourier transform: Explained
An intuitive explanation of the Fourier transform and the discrete Fourier transform (DFT), built from wrapping a signal around a circle to find its centre of mass.