What are the common methods of machine learning?

Common methods of machine learning include the following:

1. supervised learning: training models from labeled data, such as classification and regression.

2. Unsupervised learning: training models from unlabeled data, such as clustering and dimensionality reduction.

3. Semi-supervised learning: training models from some labeled data and a large number of unlabeled data.

4. Reinforcement learning: Learn the best action from the interaction between the subject and the environment, such as finding the best strategy in the game.

5. Deep learning: Using machine learning technology of multi-layer neural network can learn complex nonlinear relationships.

6. Transfer learning: By transferring the learned knowledge and skills to new tasks, the problem of less learning data is solved.

7. Meta-learning: Improve the performance of the model by learning how to learn.

These methods have specific advantages and scope of application in different scenarios and tasks.