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2. – Machine learning method where agents learn by trial and error to maximize reward.
4. – Task of predicting the category of a given input.
8. – Type of network inspired by the human brain, used in deep learning.
10. – Popular deep learning framework developed by Facebook.
11. – Step-by-step procedure used by machines to solve problems.
13. – A type of machine learning that finds patterns in unlabeled data.
15. – An individual measurable property or characteristic of data.
17. – A type of machine learning where models are trained on labeled data.
19. – Function used in neural networks to introduce non-linearity.

1. – Predicting a continuous value from input features.
3. – A type of machine learning that uses neural networks with many layers.
5. – When a model learns training data too well and performs poorly on new data.
6. – Multidimensional array used in deep learning computations.
7. – A subset of AI that allows systems to learn from data without being explicitly programmed.
9. – Collection of data used for training or testing a model.
11. – The field of computer science that simulates human intelligence in machines.
12. – Interconnected system of nodes used in deep learning.
14. – Algorithm used to update weights in neural networks.
16. – Open-source platform for machine learning developed by Google.
18. – One complete pass through the entire training dataset in ML.