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2 cards from this section. Quick, good the night before a test.
What is the main purpose of a serving framework?
Think about how models interact with users.
Name one framework used for serving TensorFlow models.
It's a specific framework tailored for a popular ML library.
What does a serving framework do in machine learning?
Think about the lifecycle of a machine learning model.
True or False: TensorFlow Serving is suitable only for PyTorch models.
Recall which ML library each framework is associated with.
You have a well-trained TensorFlow model that provides real-time predictions for a website traffic application. What steps would you take to deploy this model using TensorFlow Serving in a scalable manner?
Think about what each tool is responsible for in the deployment process.
Discuss the trade-offs between using a lightweight framework like Flask vs a more comprehensive platform like MLflow for serving models. What factors would influence your choice?
Consider the project's size, complexity, and need for tracking.
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