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What is the significance of 'latency' in model deployment?
Practice Questions
Q1
What is the significance of 'latency' in model deployment?
It measures the model's accuracy
It indicates the time taken to make predictions
It refers to the amount of data processed
It assesses the model's complexity
Questions & Step-by-Step Solutions
What is the significance of 'latency' in model deployment?
Steps
Concepts
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.
No concepts available.
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