Cloud Machine Learning Engineering and MLOps
Week 1 Quiz
1.
Question 1
What is a key difference between Data Science and ML Engineering?
You got it! ML Engineering focuses on bringing models to production.
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2.
Question 2
Why is an advantage of using a widely used ML Platform?
Many potential hires will know the technology stack
A widely used platform will be known by many users
A widely used platform will get frequent updates
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3.
Question 3
What is an advantage of Flask for ML Engineering?
You got it! Microservices are easy to create in Flask due to the minimalistic design.
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4.
Question 4
How can ML Engineering used?
You got it! ML Engineering is the process of creating ML systems that work.
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5.
Question 5
What is Continuous Delivery?
You got it! CD or Continuous Delivery is the process of ensuring code is always in a deployable state .
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6.
Question 6
What would be an example of an ML application?
You got it! OCR (Optical Character Recognition) is a good example of a Machine Learning app.
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7.
Question 7
Why would a Microservice be valuable for ML?
You got it! Microservices which are single functions are ideal to serve out ML predictions.
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8.
Question 8
What is an example of a Machine Learning Engineering platform?
You got it! Sagemaker is designed to train and deploy models.
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9.
Question 9
What problems do Machine Learning platforms solve?
You got it! Platforms allow for distributed training of large models.
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10.
Question 10
What advantage could a ML platform create for deployment?
You got it! Deploying software to endpoints that auto-scale is a key advantage.
