👉 Info math, or information theory, is a branch of mathematics that quantifies the amount of information in data. It was developed by Claude Shannon in the 1940s and focuses on measuring the uncertainty or surprise associated with random events, particularly in communication systems. The core concept is entropy, which represents the average amount of information produced by a probabilistic source, such as a message or signal. By understanding and minimizing this entropy, we can improve the efficiency of data transmission and storage. Info math also introduces the idea of mutual information, which measures how much knowing one piece of information reduces uncertainty about another. This theory has wide-ranging applications in fields like cryptography, data compression, and machine learning, providing a mathematical foundation for understanding and optimizing information processing.
