Train object detection models
I fine-tuned YOLO models in order to improve object detection (players, ball, referee) in football and tennis matches.
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While working as a Data Analyst at Horse Powertrain (Renault Group), I took part in data labeling tasks for AI projects, including classifying images of engine components as valid or non-valid. This experience helped me understand how important accurate and consistent annotation is for building reliable AI models. I worked alongside engineers from different teams, which taught me how to apply real-world context when making labeling decisions. My degree in Computer Science and Statistics, along with hands-on experience building machine learning and deep learning models in Python, gives me a strong understanding of how training data affects AI systems. I am also comfortable working with data at every stage, from collection and cleaning to labeling and validation.
I fine-tuned YOLO models in order to improve object detection (players, ball, referee) in football and tennis matches.
I labeled motor images used to train computer vision models that classify valid and non-valid motors.
Double Bachelor's Degree, Computer Science & Statistics
Software Engineer
Data Analyst