1.Model-Training:
● Choose a suitable architecture (e.g., CNN, transfer learning with pre-trained models).
● Use appropriate loss functions and optimizers for multi-class classification.
2. Evaluation
● Generate predictions on the test dataset.
● Plot the ROC Curve for each class.
Add your notebook and add your saved model in solution_Task3 .
This is a competitive task and only the best model will get 50points others will get 20points.
1.Model-Training:
● Choose a suitable architecture (e.g., CNN, transfer learning with pre-trained models).
● Use appropriate loss functions and optimizers for multi-class classification.
2. Evaluation
● Generate predictions on the test dataset.
● Plot the ROC Curve for each class.
Add your notebook and add your saved model in solution_Task3 .
This is a competitive task and only the best model will get 50points others will get 20points.