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Artificial Intelligence & Machine Learning vocabulary · Deployment and MLOps

Endpoint

Meaning in artificial intelligence & machine learning, with examples

/ˈendpɔɪnt/nounCommon term

In artificial intelligence & machine learning, endpoint means: A URL where a deployed model can be reached over a network: other software sends a request to it and receives the model's prediction or answer.

In Turkish: uç nokta, endpoint

How it is used

You create, call, scale and monitor an endpoint. Cloud platforms offer managed endpoints, and LLM providers expose endpoints such as a chat completions endpoint. Teams often keep separate endpoints for staging and production.

Example sentences

  1. The fraud model sits behind a REST endpoint that the payment service calls.

  2. The endpoint scaled down to zero overnight, so the first request this morning was slow.

Common collocations

  • call an endpoint
  • inference endpoint
  • managed endpoint
  • endpoint URL
  • deployTo put a trained model into a real system so that users or other software can send it requests and receive predictions.
  • inferenceThe stage in which a trained model is used to produce outputs for new inputs, for example answering a user's question or classifying a new photo.
  • latencyThe time between sending a request to a model and receiving its response, usually measured in milliseconds or seconds.
  • MLOpsThe practices and tools for running machine learning reliably in production: versioning data and models, automating training and deployment, and monitoring models over time.

This word in other fields

The same English word can have a different meaning in another field:

More terms: Deployment and MLOps

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