Brain-Computer Interfaces (EEG, MEG ...)

L8: MNE tutorial Part #1 - Load and Segment continuous EEG data

L9: MNE tutorial part #2 - EEG/ERP Visualization and Time-Frequency Analysis

L10: Overview of artifact and noise detection in EEG/MEG

L18 : The analysis and classification of Motor-Imagery EEG data (BCI competition IV)

PyTorch for Brain-Computer Interfaces

MNE-Python Tutorial for EEG and MEG data analysis and visualization.

How to import EEG Matlab data into MNE-Python

Importing the BCI Competition IV dataset into MNE-Python

Pybrain: MRI analysis in Python using Nipype, Nilearn and more

ROBT206: Lecture 7 - Karnaugh Map (don't cares, prime implicants)

Lecture 6: Noise and Error

ROBT206: Lecture 6 (part 2) - Four variable Karnaugh map examples

L7: ERP multivariate features

Lecture 11: Arithmetic Functions [Iterative Arrays/ Half adders/ Full adders]

L6: Event-Related Potentials

MNE for EEG/MEG signal analysis (Q&A session)

Lecture 17: Dual Support-Vector Machines

A Gentle Introduction to Brain-Computer Interfaces

L15: The scikit-learn: machine learning model selection in Python (part 3)

Lecture 8: Logistic Regression

Sylvan beach, Texas

Lecture 10: Hazard of Overfitting

Lecture 16: Linear Support-Vector Machines

What is PyTorch? [part #1]

ROBT206 - Microcontrollers - Lecture 4: Gate Circuits and Boolean Equations

L7: Event-Related Potentials - multivariate features...

The scikit-learn: machine learning in Python (part 2)

FieldTrip Toolbox - ERP visualization tutorial (silent)