Welcome to my data science and machine learning project portfolio. Here, you will find a carefully selected collection of my work, showcasing my skills in data analysis, predictive modeling, and data visualization. Each project included in this repository has been chosen for its relevance and impact and is accompanied by a detailed README that delves into the technical aspects and key findings.
Projects
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Bank Churn Prediction This project addresses the critical challenge of customer churn in the banking sector. Using a detailed dataset, I conducted thorough data cleaning and exploratory data analysis (EDA) to understand underlying trends and predictive factors. Subsequently, I explored and compared various machine learning models, such as Logistic Regression, Decision Tree, and XGBoost, to pinpoint customers with the highest risk of churn. After rigorous evaluation, the model with the best performance was selected for further refinement. The optimized model, after tuning, highlights the crucial factors influencing a customer's decision to leave the bank, thus providing invaluable insights for crafting effective retention strategies.
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Handball Goalkeeper Performance Analysis In this specific analysis, I focused on evaluating the performance of a handball goalkeeper over a season. By manually recording each shot received, I was able to identify patterns, weaknesses, and strengths in their game. The findings were visualized in an interactive dashboard in Power BI, offering a powerful tool for tactical analysis and performance improvement.
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Handball Match Goal Detection Working in a team, we developed an innovative model using neural networks, specifically YOLOv8 and DeepSort, to analyze handball match videos and determine the exact moments goals were scored. This project was complemented by creating a FastAPI API, allowing the model to be integrated into applications, and a user interface in Streamlit for an interactive and accessible experience.
I invite recruiters and colleagues to explore each project, where you will find a more detailed description, the methodology applied, key results, and conclusions. I am open to opportunities and collaborations that allow me to apply and expand my skills in data science and machine learning.