Machine learning

1. Supervised Learning
2. Unsupervised learning
3. Reinforcement learning

Supervised Learning

We enter a set of inputs and outputs, to help a program generalize it, using a best fit line/function. This is then used to predict outputs for related value.

For example :

Input	Output
1	1
2	4
3	9
4	16
.	.
.	.
.	.
10	?

This is approximation.

Unsupervised learning

No labeled data.

Density estimation is used here.

This is description.