Difference between Deep Learning and Reinforcement Learning, scenario where each should be preferred or not preferred.

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Deep Learning involves learning representations of data through neural networks, while Reinforcement Learning involves learning through trial and error with rewards.

Deep Learning is preferred for tasks with large amounts of labeled data, such as image recognition or natural language processing.
Reinforcement Learning is preferred for tasks where an agent learns through interaction with an environment, such as game playing or robotics.
Deep Learning may not be preferred for tasks with limited labeled data or when interpretability is important.
Reinforcement Learning may not be preferred for tasks with high computational complexity or when a clear reward signal is difficult to define.

Difference between Deep Learning and Reinforcement Learning, scenario where each should be preferred or not preferred.

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