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.
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.