Machine learning is
sub-categorized to three types:
·
Supervised Learning – Train Me!
·
Unsupervised Learning – I am self sufficient in learning.
·
Reinforcement Learning – My life My rules! (Hit & Trial)
1.
Supervised Learning: It is the learning in which the training data is labelled with the correct answers.
e.g., “spam” or “ham.” The two most common types of supervised learning are
classification (where the outputs are discrete labels, as in spam filtering)
and regression (where the outputs are real-valued).
2.
Unsupervised learning: It is the learning in which we are given a collection of unlabeled data, which we
wish to analyze and discover patterns within. The two most important examples
are dimension reduction and clustering.
3.
Reinforcement learning: It is the learning in which an agent (e.g., a robot or controller) seeks to learn the
optimal actions to take, based the outcomes of past actions.
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