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What is model deployment in the context of machine learning?

Practice Questions

Q1
What is model deployment in the context of machine learning?
  1. Training a model on a dataset
  2. Integrating a model into a production environment
  3. Evaluating model performance
  4. Collecting data for training

Questions & Step-by-Step Solutions

What is model deployment in the context of machine learning?
  • Step 1: Understand that a machine learning model is a program that has learned from data.
  • Step 2: Realize that after training the model, it needs to be used in real-world situations.
  • Step 3: Model deployment is the process of taking this trained model and making it available for use.
  • Step 4: This means putting the model on a server or in an application where it can receive new data.
  • Step 5: Once deployed, the model can make predictions based on the new data it receives.
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