Types of Learnings in ML

Broadly there are three different types of Machine learning algorithms. 

(1) Unsupervised Learning : There is no help from the user for the computer to learn. Imagine learning without a teacher or any sort of guidance. 

(2) Supervised Learning : Imagine learning with a teacher. The process of an algorithm learning from the training dataset can be thought of as a teacher supervising the learning process. We know the correct answers, the algorithm iteratively makes predictions on the training data and is corrected by the teacher.

(3) Reinforcement Learning : This is the closest to how humans learn, imagine a kid learning how to walk, or how you learnt the game of chess. In this case, the algorithm or the agent learns continually from its environment by interacting with it. It gets a positive or a negative reward based on its action.

Different types of learnings in ML. (source)

Looking forward to your comments or questions! Thank you.

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