Core Basics in ML, Signal Processing, and More

  • Static PDF file: Lecture Notes
  • Dynamic PDF file: You can access the lecture PDF here on Overleaf. In the future, a full Jupyter Book version will be available for interactive learning.

Inspired by The Fall by Albert Camus, this channel explores how vectors—the building blocks of ML “fall” into patterns, signals, and representations, uncovering hidden structures in data.

Short Tutorial on Cross-Spectrum and Coherence in EEG

In my 2018 PhD progress report, I discussed the cross-spectrum and coherence in EEG. You can view it [here]

Tutorial on EEG Time-Frequency Representation in the Context of Envelope Following Response (EFR)

This tutorial is part of the supplementary materials for my PhD thesis. It focuses on EEG time-frequency representation in the context of the Envelope Following Response (EFR), also known as the Frequency Following Response (FFR). Topics include induced and evoked responses, phase-locked and non-phase-locked power, and more. Chekt it out here. Enjoy! [here]