Probability Distributions for Machine Learning

Learn the most important probability distributions used in Machine Learning and Data Science. This section explains Normal, Binomial, Poisson, and Uniform distributions with intuition, formulas, and real-world ML examples.

📄️ Normal

A deep dive into the Normal Distribution, the Central Limit Theorem, and why Gaussian assumptions are the backbone of many Machine Learning algorithms.

📄️ Binomial

Understanding the foundations of binary outcomes: The Bernoulli trial and the Binomial distribution, essential for classification models.

📄️ Poisson

Understanding the Poisson distribution: modeling the number of events occurring within a fixed interval of time or space.

📄️ Uniform

Exploring the Discrete and Continuous Uniform distributions: the foundation of random sampling and model initialization.