Model Development:

• Two different approaches were employed for sales prediction: linear regression and gradient boosting.

• Linear regression was chosen to model the relationship between the input features (quantity, price, etc.) and the target variable (sales).

• Gradient boosting, an ensemble learning technique, was utilized to enhance the prediction accuracy by combining multiple weak prediction models (decision trees).

• Hyperparameter tuning was performed to optimize the performance of the models.