I'm an AI/ML engineer with over five years of programming experience in Python. I've tackled data science projects that allowed me to apply my knowledge in many different business settings, delivering important insights through the development of machine learning models and data visualization pipelines. I'm currently working on the intersection between ML and Cybersecurity. Most of my work is available on GitHub.
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This project focuses on forecasting weekly retail sales using the Walmart Store Sales dataset. The main objective is to predict future sales from historical store- and department-level data, with an emphasis on improving WMAE performance while keeping experiments reproducible and easy to compare through MLflow-tracked models, convergence plots, and feature engineering iterations.
The goal of this project is to optimize solar power generation with machine learning by analyzing the environmental factors that influence the efficiency of solar panels. A key focus is on the impact of precipitation on generated solar power. By understanding this relationship, we can better predict and optimize solar power generation under varying weather conditions.
This project undertakes a sentiment analysis to compare the audience’s emotional responses towards movie directors. An analysis of movie reviews made by users at Letterboxd is carried out, aiming to explore how the sentiments differ for directors in different genres and levels of popularity.
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