Answer:
In summary, AI learning is a broader field that encompasses various approaches to machine learning, while deep learning is a specific approach that uses complex neural networks to learn and recognize patterns in data.
Step-by-step explanation:
AI learning and deep learning are both subfields of artificial intelligence, but they differ in terms of their approach and complexity.
AI learning involves the use of algorithms to enable machines to learn from data and make decisions based on that data. This can include supervised learning, unsupervised learning, or reinforcement learning. In supervised learning, the machine is trained on labeled data, while in unsupervised learning, the machine finds patterns and relationships in unlabeled data. Reinforcement learning involves the machine learning through trial and error, receiving feedback in the form of rewards or penalties.
Deep learning, on the other hand, is a subset of AI learning that involves the use of neural networks with multiple layers to learn and recognize patterns in complex data. It is particularly effective in tasks such as image recognition, natural language processing, and speech recognition. Deep learning requires a large amount of data and computing power to train the neural networks effectively.