Entropy, in Shannon's terms, means the amount of uncertainty or surprise in information. ๐ค
For example, if you flip a coin, there are two possible outcomes: heads or tails. That's low entropy! But if you have a box of different-colored balls, predicting which one you'll pull out is harder, creating higher entropy! ๐ฒ
Shannon created a way to calculate this uncertainty using a formula that helps engineers design systems that reduce errors in communication. This concept is super useful in
computer science and telecommunications! ๐
So next time you flip a coin, remember that you're playing with information entropy! ๐ช