You can classify the algorithms using different methods
supervised, unsupervised, semi-supervised, reinforcement learning]
online vs batch]
instance-based vs model-based]
You feed labeled data to the algorithm.
Regression are the kinds of problems that can be solved with supervised learning. Some popular algorithms
Training data is unlabeled. System tries to figure out the relationships.
anomaly detection and
Dimensionality Reduction are good problems that can be solved with this type of learning. Some popular algorithms
Algorithms that can learn with partially labelled data and lots of unlabeled data. Some examples of algorithms
Learning system (
agent) can observe the environment, select and perform actions and get
penalties. It must learn by itself to get the most reward over time (
policy). Thus a
policy defines what action the
agent must take in a given situation.
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