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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What platform would you use to create a Jupyter Notebook?
💡 Hint: Think about AWS services for machine learning.
Question 2
Easy
What does REST API stand for?
💡 Hint: Consider APIs and state transfer.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What service allows you to create and manage Jupyter Notebooks?
- AWS Lambda
- AWS SageMaker
- GCP Dataflow
💡 Hint: Think about AWS services focused on machine learning.
Question 2
Is BigQuery ML used for SQL-based machine learning?
- True
- False
💡 Hint: Recall the primary function of BigQuery.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a model in SageMaker that predicts stock prices based on historical data. Outline each step from data loading to deployment.
💡 Hint: Use the steps of model training discussed in class.
Question 2
Create a data pipeline using GCP Dataflow to continuously process user behavior data from a live feed. Describe how you would implement it.
💡 Hint: Focus on aspects of streaming and how data flows through the pipeline.
Challenge and get performance evaluation