Sleep Classification with Python Using EEG, Sklearn and MNE - Part 1
Offered By: Yacine Mahdid via YouTube
Course Description
Overview
Explore the second part of an EEG sleep stage classification tutorial using Python, Sklearn, and MNE. Learn how to expand the classifier by incorporating data from 10 additional participants, introducing a new class, and implementing Leave-One-Subject-Out cross-validation. Dive into the code implementation, starting with an introduction and project overview before delving into the technical aspects. Gain insights on power spectral density (PSD) through a recommended blog post. Conclude with a summary of the achieved results and compare them to the previous iteration covered in the linked first part of the series.
Syllabus
- Introduction:
- Project Overview:
- Code:
- Conclusion:
Taught by
Yacine Mahdid
Related Courses
How to Win a Data Science Competition: Learn from Top KagglersHigher School of Economics via Coursera Data Science: Machine Learning
Harvard University via edX Visual Machine Learning with Yellowbrick
Coursera Project Network via Coursera Regression Analysis with Yellowbrick
Coursera Project Network via Coursera Support Vector Machines in Python, From Start to Finish
Coursera Project Network via Coursera