🔤 ML Terms

Student Info

📋 Instructions:

✅ Drag each term from the left column to match it with the correct definition on the right.

🔄 You can replace a term by dragging a new one to the same definition box.

📊 Submit when done to see your score!

📝 Terms

Testing Data
Overfitting
Precision
F1 Score
Model Deployment
Endpoint
Training Data
Recall
Underfitting
Confusion Matrix
Validation Data
Accuracy

📖 Definitions

The dataset used to train an ML model.
The dataset used to tune the model's hyperparameters.
The dataset used to evaluate the performance of the model.
A modeling error where the model performs well on training data but poorly on new data.
A modeling error where the model is too simple to capture the underlying patterns in the data.
The ratio of correctly predicted observations to the total observations.
The ratio of correctly predicted positive observations to the total predicted positives.
The ratio of correctly predicted positive observations to all observations in the actual class.
The weighted average of precision and recall.
A table used to evaluate the performance of a classification model.
The process of making an ML model available for use in production environments.
A URL where the deployed model can be accessed.