In this project, the revenue of restaurants is predicted from Kaggle competition data (https://www.kaggle.com/competitions/restaurant-revenueprediction). The main challenge was to investigate various models to predict the revenue and provide a recommendation to TFI on which model to use for future predictions.

In this project, creditworthiness ratings are predicted using several ML algorithms to prevent financial fraud. During the analysis, the model parameter optimization is performed to improve the ML model performance. Further different measures are compared to select the most optimized model for the respective dataset.