Data Science and Business Analytics professional with a diverse background. Proficient in advanced analytical tools and techniques, with a strong focus on delivering actionable insights and strategic business solutions. Experienced in biomedical research, programming and data analysis.
This master's thesis analyses data from earthquakes that ocurred in 2023 and uses machine learning and deep learning models to predict the magnitude of earthquakes.
Rosacea and psoriasis are two chronic inflammatory skin diseases with similar facial symptons. This study focused on the search for predictive models for rosacea and psoriasis, using various architectures of Convolutional Neural Networks (CNNs) pre-trained through Transfer Learning.
This project involves creating a database to store information on the 2021 Formula 1 championship, focusing on drivers, circuits, teams, employees, and sponsor companies. The data will be organized using an entity-relationship model and logically designed with considerations for keys, attributes, and normalization. The information will be sourced from the official F1 website, with the exception of employee data.