# Machine Learning - What is Machine Learning?

Here is a plot of house prices versus its square footage.

Our predictions are based on the best-fit line that we draw after plotting various data points on the XY plot. You will feed the known data to the machine and ask it to find the best-fit line. Once the machine finds the best-fit line, you will feed a known house size, i.e. the Y-value in the above curve, to test its suitability. The estimate X-value, the price of the house, will now be returned by the machine. The diagram can be extrapolated to find out the price of a house with 3000 square feet or even larger. This is called regression in statistics, particularly linear regression since the relationship between X & Y data points is linear.

In many cases, the relationship between the X & Y data points may not be a straight line, but rather a curve with a complex equation. Here is a figure showing one such application plot. The goal now is to find the best fitting curve that can be extrapolated to predict future values.

*Source:*

*https://upload.wikimedia.org/wikipedia/commons/c/c9/*

This is exactly what Machine Learning is about. You use known optimization techniques to find the best solution to your problem.

Let's take a closer look at the different categories of Machine Learning.

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