CNN and RNN Using PyTorch

Abstract

Probability and random variables are an integral part of computation in a graph-computing platform like PyTorch. Understanding probability and the associated concepts are essential. This chapter covers probability distributions and implementation using PyTorch, as well as how to interpret the results of a test. In probability and statistics, a random variable is also known as a stochastic variable, whose outcome is dependent on a purely stochastic phenomenon, or random phenomenon. There are different types of probability distribution, including normal distribution, binomial distribution, multinomial distribution, and the Bernoulli distribution. Each statistical distribution has its own properties.