This repository provides a practical tutorial on probability distributions for deep learning researchers. It covers discrete and continuous distributions including Uniform, Bernoulli, Binomial, Poisson, Exponential, Gaussian, and Beta, with Python implementations and visualizations. The material explains how distributions relate to ML concepts like binary cross entropy and conjugate priors in Bayesian inference.