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.