Heart Disease Predictions

In the heart disease prediction project, I utilized Python programming language along with machine learning techniques to develop a model that predicts the likelihood of an individual developing heart disease. The goal of the project was to create a tool that could assist healthcare professionals in early identification and intervention for individuals at high risk.I gathered a comprehensive dataset comprising crucial medical parameters such as trestbps (resting blood pressure), cholostrol levels, blood pressure, gender, thalach (maximum heart rate achieved), glucose levels, and more. The dataset was preprocessed by handling missing values, normalizing features, and performing necessary transformations to enhance the accuracy of the model.For this project, I employed two machine learning models: Decision Tree and Linear Regression. These models were chosen due to their interpretability and ability to capture non-linear relationships within the data.By completing this heart disease prediction project , I demonstrated proficiency in Python programming, employed decision tree and linear regression models, and utilized visualization tools like Tableau and Streamlit.

Link For the project is given below

• Link for the Project