The Law of Large Numbers is a theorem within probability theory that suggests that as a trial is repeated, and more data is gathered, the average of the results will get closer to the expected value. As the name suggests, the law only applies when a large number of observations or tests are considered.| DeepAI
Central Limit Theorem states that the distribution of observation means approaches a normal distribution model as the sample size gets larger.| DeepAI
A discrete random variable is a random variable with a limited and countable set of possible values.| DeepAI
Binomial distribution is the sum of all successes in repeated independent trials conducted on an infinite, identical population.| DeepAI
Probability in deep learning is used to mimic human common sense by allowing a machine to interpret phenomena that it has no frame of reference for.| DeepAI
