This project demonstrates a simple implementation of a Linear Regression model using Python. The model is trained to make predictions based on a dataset loaded from a .pkl (Pickle) file.
#What’s Inside: -Loading and preprocessing a dataset from a Pickle file -Training a Linear Regression model using scikit-learn -Evaluating the model’s performance -Making predictions on new data -Saving and loading the model for reuse