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Machine learning as the word defines itself, we have a machine who wants to learn, and just like
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humans, machines also have a different method for learning something.
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We have supervised learning.
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They have unsupervised learning.
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And finally, we have reinforcement learning. In this Supervised learning.
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We have different techniques, like regression and we also have classifications just like image classifications,
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If you have any image processing field and you need to have somehow classifications of your data.
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then Supervised learning going to be the best for unsupervised learning.
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We have like a big data validation.
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Whenever you are dealing with some big data and you want to label them, that's the best method to use
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here.
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We have targeted marketing, customer segmentation, and more. For reinforcement learning.
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It deals with robot navigation and mapping, skill acquisition.
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When we have some system or a kind of robot that wants to learn a new skill, then this is the learning
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method that we need to use.
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We have a game A.I.
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We have a real time decision making and finally the learning tasks.
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So let's get to know each of them better with some examples, of course.