What are the methods of machine learning?

Some several different methods or techniques can be used for machine learning, including:

1. Supervised learning: This involves training a model on labeled data, where the correct output is provided for a given input. The model makes predictions based on this input-output mapping.
2. Unsupervised learning: This involves training a model on unlabeled data, allowing the model to discover patterns and relationships in the data.
3. Semi-supervised learning: This involves training a model on a combination of labeled and unlabeled data.
4. Reinforcement learning: This involves training a model to take actions in an environment in order to maximize a reward.
5. Deep learning: This involves training artificial neural networks on large amounts of data.
6. Transfer learning: This involves using a pre-trained model on a new task, using the features learned from the original task as a starting point.
7. Online learning: This involves training a model on data that is continually streamed, allowing the model to update in real-time.