Loss Functions Part - 1
Introduction First let us understand, how the machine learns from the given data. Actually, it is learning the relationship within the data. There are 3 steps in which the machine learns first it will predict an output. Mainly the first prediction is mostly random. Then it calculates the error and then learns and then this process happens many times. The error goes on reducing cost function is also known as loss function. If the cost functions are convex, then it is easier to calculate the error and minimize it as the global and local minima. But not all cost functions are convex in nature. We will understand the error functions slowly by looking at examples by observing their graphs. Loss Functions Why we need Loss Functions? Loss function actually measures how good a prediction the result/outcome made by the model is so, it’s a measure of how good is the mode l. Is Cost Function the same as the Loss function? In our day-to-day ...