Probability provides the mathematical foundation to model uncertainty, make predictions, evaluate models, and make data-driven decisions in the dynamic and often uncertain environments where AI and data science are applied. Concepts from probability are applied in various contexts, including data analysis, decision-making, and modeling in AI and machine learning.
Below are the several concepts used when it comes to data science and AI:
Probability Distributions: Understanding different types of probability distributions (e.g., normal, binomial, Poisson) is essential for modeling and analyzing data. These distributions help in understanding the likelihood of different outcomes.