Covers Gaussian Mixture Models, Denoising, Data Classification, and Spike Sorting using Principal Component Analysis.
Explores parametric spectrum estimation methods, including line and smooth spectra, and delves into heart rate variability analysis.
Explores air pollution analysis using wind data, probability distributions, and trajectory models for air quality assessment.
Covers the basics of LabVIEW, including its importance, history, functions, and tools available.
Covers dimensionality reduction, clustering, and density estimation techniques, including PCA, K-means, GMM, and Mean Shift.
Explores maximum likelihood inference, comparing models based on likelihood ratios and demonstrating with a coin example.
