1. Preprocessing
2. Hyperparameters
3. Validation
4. Overfitting
5. Deployment
Preparing data before using it in a model.
When a model works well on training data but poorly on new data.
Settings that control how a model learns.
Testing a model to check its accuracy.
Making a model ready for real-world use.
Drag the cards on the right so each lines up with the correct item on the left.
