Grid search cross-validation (GridSearchCV) is a technique used in machine learning to find the optimal hyperparameters for a model and it involves defining a grid of hyperparameters to search over. It automates the process of tuning hyperparameters, which can be tedious and time-consuming if done manually and helps in finding the best combination of hyperparameters that yields the best performance for the given dataset and model.
https://www.kaggle.com/datasets/johnsmith88/heart-disease-dataset
git clone https://github.com/MartinKalema/Hyperparameter-Tuning-GridSearchCV