I created machine learning classifiers to predict the antimicrobial activity of peptides. It was an end-to-end project in which I did the data pre-processing, feature engineering, training, hyperparameter tuning, and deployment of the best model as a web application with Streamlit.
In this project, we captured sentiments of replies to tweets from two Ecuadorian presidential candidates in the 2021 elections (@LassoGuillermo and @ecuarauz). A model of artificial neural networks was used to classify tweets considering their sentiment as positive, negative, or neutral.
In this project, I created machine learning classifiers (Logistic Regression, Random Forest, and XGBoost) to evaluate the activity of molecules that have been experimentally tested to bind or not bind to Beta-Lactamases. Also, I implemented a web service with the best model.
This project is a computational study of the structural changes of two Cereblon protein mutations using Molecular Dynamics and Quantum Mechanics simulations.
In this project, we created a plant disease detector based on convolutional neural networks, trained to recognize two types of maize infectious diseases - Common rust of corn and Northern corn leaf blight.