What is Hyperparameter?
A setting chosen by engineers before training — not learned from data — that controls how learning runs.
Hyperparameter explained in plain English
Analogy
Hyperparameters are like the oven temperature and cooking time on a recipe — they are not ingredients, but they determine whether the dish turns out well or burns.
Example
Choosing learning rate, batch size, and number of training epochs for a new chatbot are all hyperparameter decisions.
How is Hyperparameter used?
AI engineers tune hyperparameters when building everything from recommendation engines to large language models. Getting them wrong can mean a model that never learns properly or takes weeks instead of days.
Common misconceptions about Hyperparameter
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