Gabriel Melo
PhD Student · Machine Learning · Graphs & Uncertainty
PhD Student · Machine Learning · Graphs & Uncertainty
As part of my academic and research interests, I am currently involved as a teaching assistant in the following courses:
Reproducing Kernel Hilbert Spaces; Kernel machines for regression, classification and dimensionality reduction; kernel design and kernel learning
Models and estimators, Cramer-Rao Bound, Fisher Information, hypothesis testing, confidence intervals, bayesian methods
This course covers the foundations of machine learning, including supervised and unsupervised learning, regression, classification, clustering, and neural networks.
This course introduces students to the field of NLP, covering text preprocessing, word embeddings, sequence models, and deep learning approaches for text analysis.