Normal Distribution and Machine Learning

Normal Distribution is an important concept in statistics and the backbone of Machine Learning. A Data Scientist needs to know about Normal Distribution when they work with Linear Models(perform well if the data is normally distributed), Central Limit Theorem, and exploratory data analysis. As discovered by Carl Friedrich Gauss, Normal Distribution/Gaussian Distribution is a continuous probability distribution. It has a bell-shaped curve that is symmetrical from the mean point to both halves of the curve. A continuous random variable "x" is said to follow a normal distribution with parameter μ(mean) and σ(standard deviation), if it's probability density function is given by, This is also called a normal variate.