Across
- 1. Facts & statistics collected together for reference
- 3. Top and first node of a decision tree
- 5. Occurs due to data being used that does not accurately represent what is being modeled
- 6. Computer systems that are able to learn and adapt by using algorithms
- 8. When the output of a machine learning model favors some things and excludes others
- 9. A representation of a real-world context
- 12. Parts of a decision tree
- 13. When data being used to train a model reflects bias that exists in society
- 15. Usually represent a single class & provides a predicted label
- 16. Information used to test how well a ML model works
- 19. Removing outliers, handling missing values, and resolving inconsistencies
- 22. The process of assigning data to a class by applying labels
- 23. A category that data can be assigned to
- 24. Observations that can be made about an object
Down
- 2. Set of technologies that enable computers to perform a variety of functions
- 4. These contain decisiong that split data in two directions
- 7. Structured process for developing, deploying, and managing AI models
- 10. Process or set of rules to be followed in calculations, especially by a computer
- 11. Applied to a single piece of data to indicate which class it belongs to
- 13. ML technique that uses labeled datasets to train algorithms to recognize patterns and predict outcomes
- 14. Type of AI that uses generative models to create new data
- 17. Collection of lebeled information used to train a ML model
- 18. Type of model created using supervised learning to classify data
- 20. A type of model relying on a massive amount of data to detect patterns to create a representation
- 21. A way of building AI systems using statistics
- 22. Field of AI that allows computers to understand and interpret visual information