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The machine learning algorithm are further divided into Supervised machine learning algorithms, unsupervised machine learning algorithms, Semi-supervised machine learning algorithms, Reinforcement machine learning algorithms.
Supervised machine learning algorithm can apply what has been learned in the past to new data using labelled examples to predict future events.
Unsupervised machine learning algorithms are used when the information used to train is neither classified nor labelled.
Semi-supervised machine learning algorithms fall somewhere in between supervised and unsupervised learning, since they use both labelled and unlabelled data for training – typically a small amount of labelled data and a large amount of unlabelled data.
Reinforcement machine learning algorithms is a learning method that interacts with its environment by producing actions and discovers errors or rewards.