Home

Machine Learning/Advanced Digital Signal Processing

This subject is an introductory course on theoretical and practical concepts to start with machine learning as well as advanced digital signal processing.

Lecture (Invited speaker): Introduction to Principal Component Analysis (PCA)

Date: 28/10/2017

Info

Slides

Lecture (Invited speaker): Kernel PCA

Date: 28/10/2017

Info

Slides

Lecture (Invited speaker): Recognition and interpretation of seismic-volcanic patterns under realistic conditions using adaptive learning techniques

Date: 21/10/2017

Info

Slides

Thesis proposal

Ordinary lecture: Writting a scientific paper

Date: 21/10/2017

Slides here.

Interesting related readings here.

LaTex templates and installers.

Ordinary lecture: Matrix Algebra for pattern recognition/Digital signal processing

Date: 07/10/2017

- Matrix algebra exercises: pdf

- Signal processing exercises: pdf

- Matrix coobook: pdf

- Pattern recognition books: web pdf

- Pattern recognition glossary: web pdf

- Matrix coobook: pdf

- Pattern recognition techniques: pdf

- Variable transformation and data representation: pdf

Lecture (Invited speaker): Multiclass Case-based reasoning methodology for medical applications

Date: 30/09/2017

Info

Thesis

Slides

Lecture (Invited speaker): Part-of-speech identification via metaheuristics

Date: 19/08/2017

Info

Slides