Across
- 2. Data used to evaluate model performance
- 5. Brain-inspired computing model
- 7. Model memorizes training data too well
- 11. Trainable parameters of a model
- 13. Difference between predicted and actual output
- 14. Learning without labeled data
- 15. Predicting continuous numerical values
- 16. Improving model performance by tuning parameters
Down
- 1. Known output in supervised learning
- 3. Learning using labeled data
- 4. Assigning inputs to predefined categories
- 6. Learning through rewards and penalties
- 8. Function that introduces non-linearity
- 9. Machine learning using multiple hidden layers
- 10. Input variable used to train a model
- 12. Grouping similar data points together