Project 1

This Project aim was to find the best accuracy among mentioned model for heart dataset in any Pharma Company were accuracy is deciding factor.

The project is proceeded by following steps:-

1. Load the Dataset: Load the provided dataset.
2. Preprocess the Data: Handle missing values (if any), encode categorical variables, and normalize or scale the data.
3. Split the Data: Split the data into training and testing sets.
4. Apply Machine Learning Models: Train and evaluate five different machine learning models:
   • Logistic Regression
   • K-Nearest Neighbors Classifier (KNN)
   • Support Vector Machine (SVM)
   • Decision Tree Classifier
   • Random Forest Classifier
5. Compare Accuracy: Compare the accuracy of these models to determine which one performs best.