Glossary

WhatisMachineLearningModel?

Software Development Glossary & Terms

Machine Learning Model

Definition.

Machine Learning Model: A file that has been trained to recognize certain types of patterns over a set of data.

In More Detail

A trained model is a function fitted to historical data. That framing explains its main limitation: it can only reflect patterns present in what it was shown, and it has no way to know when it is being asked about something new.

So the metric that matters is performance on data held back from training, not on the data it learned from. A model that scores well on its own training set and poorly on a holdout has memorised rather than generalised, and it will disappoint in production.

In Practice

In my Fake News Detection project, this is the trained TensorFlow/LSTM artifact that gets loaded by a FastAPI or Django inference endpoint at request time — the model itself is inert until it's wired into a real serving pipeline, which is usually where projects underestimate the remaining work.

Related Terms

Browse the full software development glossary, or see the frequently asked questions.

If you are working out whether this applies to your own project, the case studies show where it turned up in real builds, services lists what I take on, and pricing gives the starting figures.

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