stroke prediction

roject: Stroke Prediction Using Machine Learning

Performed data preprocessing to clean and prepare the dataset for analysis.

Conducted Exploratory Data Analysis (EDA) to identify key patterns and insights.

Implemented multiple machine learning models, including Logistic Regression, Random Forest, SVM, and Decision Tree Classifier.

Achieved an accuracy of 94% in stroke prediction.

Evaluated model performance using various metrics and optimized hyperparameters to enhance accuracy.