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Machine Learning
Machine learning is a researchfield that came back to life in 1980 and is a part of artifical inteligence. Machine learning uses algorithms to detect paterns, make predictions or sort data.
Within machine learning there are three diffrent kinds of approuches, supervised learning, unsupervised learning and reinforced learning. Within this chapter we will explore these diffrent kinds of way the machine learns.
For supervised learning to work, the machine will need to be given labeld data and the expected output. This kind of learning works best for regression and classification.
Unsupervised learning works with unlabeled data and the machine will try and find paterns on his own.
With reinforcement learning the machine will learn by trial and error and with the feedback provided.
Within machine learning there are three diffrent approuches of machine learning, classification, clustering and regression.
Sorting data based on the category of the data, there is no overlap.
Clustering is based on the properties of the data, data can have multiple properties.
Regression is used to determine the strength of the relationship between depending values.