ML vs AI vs DL
Across
- 2. ML task of assigning labels to inputs
- 8. ML task focused on predicting continuous values
- 9. Backbone of deep learning models
- 10. Problem in both ML and DL where the model fits noise
- 12. Intelligence Broad field aiming to simulate human intelligence
- 13. AI field focused on interpreting images and videos
- 16. Learning Subset of ML using neural networks with many layers
- 18. Ability of a model to perform well on unseen data
- 19. Step-by-step procedures for solving ML problems
Down
- 1. AI field focused on understanding human language
- 3. Key goal of AI to perform tasks without human intervention
- 4. Popular framework for deep learning models
- 5. Learning type where models learn through rewards and penalties
- 6. Learning Subset of AI focused on learning from data
- 7. Type of learning where models learn from labeled data
- 11. Inputs used by models to make predictions
- 14. Type of learning where models find patterns in unlabeled data
- 15. Key components of deep learning architectures
- 16. Core element used for training ML and DL models
- 17. Training method used in deep learning