Cardiovascular Disease Prediction

The project aimed to build a Machine Learning classification model that predicts whether a person belongs to the cardiovascular disease class based on health-related features such as:

🔹 Age

🔹 Weight & Height

🔹 Blood Pressure

🔹 Cholesterol

🔹 Glucose Level

🔹 Smoking & Alcohol Consumption

🔹 Physical Activity

Throughout the project, I gained practical experience in:

📊 Data Analysis & Exploratory Data Analysis (EDA)

🧹 Data Cleaning & Preprocessing

📈 Data Visualization

⚙️ Feature Engineering

🔄 Train/Test Split & Feature Scaling

🤖 Machine Learning Classification

📌 Model Evaluation

📉 Confusion Matrix, Precision, Recall, F1-Score & ROC-AUC

This project was a great opportunity to transform the concepts I learned into a real-world Machine Learning application, while improving my problem-solving, data analysis, and model-building skills.

I’m truly grateful to NTI for providing such a valuable technical learning experience and hands-on training. 🙏

A special thank you to my amazing instructor

‏‏Mohamed Ammar‏‏

‏‏Nancy Ahmed‏‏

for guidance, support, and valuable feedback throughout the training and project. Your effort and mentorship played an important role in this journey. ❤️

And a big thank you to everyone who supported me along the way.

This is not the end — it’s another step toward becoming a stronger Data Scientist / Machine Learning Engineer. 🚀