Within the domain of unsupervised machine learning is unsupervised clustering, also known as “ clustering analysis,” which enables organizations to group unlabeled data into meaningful categories.

so H(Fair) = 1 H (F a i r) = 1 for a fair coin, and we say it has 1 bit of entropy if you re-do the calculation with an unfair coin, say a coin with a 99% chance of coming up heads, you get H(Unfair) ...

Machine learning can be supervised, unsupervised, or semi-supervised. In supervised learning, models are trained on labeled data, meaning the input data is paired with the correct output.

Models like OpenAI o1 and OpenAI o3‑ mini advance this paradigm. Achieving more than 60% accuracy in its responses, the pre-training of ChatGPT 4.5 integrated machine learning and system teams.