Mestrado Integrado em Engenharia Biomédica | Instituto Superior Técnico, Universidade de Lisboa | 2020-2021
This course aims at providing insight and knowledge on state-of-the-art machine learning and data mining techniques, and its broad application to a diversity of real-world data sets and problems. Application examples addressed in the course include sensor-based, web-based, computer vision, biomechanics, biological systems, bioinformatics, human-centered health monitoring, prediction and disease prevention… Students completing the course are expected to: 1) understand the fundamental concepts, and challenges of machine learning and data mining techniques; 2) have a clear understanding of its applicability and empowerment over a broad range of areas transversal to most engineering courses, in particular, the several scientific areas of the Biomedical Engineering Department; 3) be able to solve real-world problems in the several scientific areas and application domains, with a proper understanding of what the tools mean, when and how to apply them, and critically evaluate and compare the solutions provided. provided by the tutors, with the purpose of solving practical problems, presenting their results in written and oral form for group discussions.
Machine Learning, Data Mining Techniques, Jupyter Notebooks
Classes: schedule
Tutoring: To be defined with tutors
Method: Online + In-person (when applicable)
Classes: Theoretical lectures + Labs + Project
Prof. Ana Luisa Nobre Fred (afred@lx.it.pt)
| NB code | Subject | Date | Lecturer | Chapter | Notebook |
|---|---|---|---|---|---|
| C010 | Setup your Python Workspace | X/10/2020 | Prof. | C - Signal Processing |   |
| A002 | Science Journal | X/10/2020 | Prof. | A - Introduction to Signal Acquisition | |
| E002 | Signal Classification Using Supervised Learning | X/10/2020 | Prof. | E - Classification | |
| E003 | Classification of Human Activity Data | X/10/2020 | Prof. | E - Classification | |