Student Work (Dissertation) | COMP9005 Part 2 ML Model Training on Health Data | University of Kent

Student | Client Work (Dissertation) | COMP9005 Part 2 Predictive Modeling in Medical AI | MSc AI Output Video | University of Kent

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🚀 Video Details:
📊 Part 2 – Model Evaluation & Results | Machine Learning in Medical Data
This short video showcases Part 2 of a dissertation from the University of Kent MSc program in Advanced Computer Science, titled "Machine Learning Applied to Medical Data."

🚑 Part 2 Focus:
– Model training and testing (SVM, Logistic Regression, RF)
– Classification metrics (accuracy, precision, recall, F1-score)
– Confusion matrix and ROC curve visuals
– Performance analysis for medical diagnosis models
– Toolkits used: Python, Scikit-learn, Seaborn

📘 Module: COMP9005 – Dissertation
🏫 University: University of Kent
📍 Location: Canterbury, England
🎓 Degree: MSc Advanced Computer Science

This part visualizes the impact of preprocessing from Part 1 and shows the performance of the models built to assist predictive healthcare.

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