ML vs AI vs DL

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