What is the significance of 'latency' in model deployment?

Practice Questions

Q1
What is the significance of 'latency' in model deployment?
  1. It measures the model's accuracy
  2. It indicates the time taken to make predictions
  3. It refers to the amount of data processed
  4. It assesses the model's complexity

Questions & Step-by-Step Solutions

What is the significance of 'latency' in model deployment?
  • Step 1: Understand that latency is the time delay between sending a request and receiving a response.
  • Step 2: Recognize that in model deployment, latency measures how quickly a model can process input data.
  • Step 3: Realize that lower latency means faster predictions, which improves user experience.
  • Step 4: Consider that high latency can lead to frustration for users waiting for results.
  • Step 5: Conclude that managing latency is important for making sure users are satisfied with the model's performance.
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