supervised,unsupervised and reinforcement in machine learning

supervised learning:

supervised learning is learning in which we teach the machine already.

In supervised learning, we fetch the collection of data set into machine. With the help of experience of data, the machine identifies a new data pattern.

In Supervised machine learning, we are given a data set and machine know what our correct answer looks like.

A supervisor or teacher is provided to the machine  and some data is already tagged with the correct answer

ex: Suppose you given a basket filled with a different kind of  vegetables now first train the machine one by one with all vegetable

* colour of the object is white and on top have some green leaves: Radish

*The shape of the object is rounded and colour brown: potato

after training the machine with data now you give a potato to the machine. Machine identify 

the name of the object.

supervised learning is classified into two categoris algorithms:

1: regression-In a regression problem we try to predict the result within a continuous result the output variable is a real value such as dollars and weight

2: classification-In a classification instead of continuous we predict the result within a discrete result

*A classification problem is when the output data is a category such as Radish and potato