AWS Certified Data Analytics Specialty 2021 - Hands-On! - Amazon Machine Learning Service

The video tutorial provides an overview of Amazon Machine Learning (ML), highlighting its features, capabilities, and limitations. It explains how Amazon ML offers visualization tools and wizards for model creation without coding, and discusses its use cases such as fraud detection, demand forecasting, and social media classification. The tutorial also covers the cost model, emphasizing the pay-as-you-go approach, and outlines the limitations regarding data size and job concurrency. Additionally, it identifies anti-patterns and tasks unsuitable for Amazon ML, such as deep learning and large-scale data processing.

What is a key feature of Amazon ML that simplifies model creation?

• It requires manual server provisioning.

• It only works with on-premise data.

• It uses visualization tools and wizards.

• It requires extensive coding knowledge.

Which of the following is NOT a limitation of Amazon ML?

• Limited algorithm choices.

• Outdated compared to deep learning.

• Limited to 100 GB of training data.

• Requires manual server management.

Which use case is Amazon ML particularly suitable for?

• Deep learning tasks.

• Sequence prediction.

• Fraud detection.

• Unsupervised clustering.

How does Amazon ML charge users?

• Pay for what you use.

• Based on the number of users.

• Annual subscription.

• Flat monthly fee.

What is a major limitation of Amazon ML regarding data size?

• It is limited to 100 GB of training data.

• It requires data to be in a specific format.

• It can process unlimited data without restrictions.

• It can handle petabytes of data.

Which task is NOT suitable for Amazon ML?

• Demand forecasting.

• Binary classification.

• Deep learning.

• Regression analysis.

What should you do if you need to run more than five simultaneous jobs on Amazon ML?

• Reduce the size of your data.

• Upgrade to a premium account.

• File a support ticket to lift the restriction.

• Wait for the current jobs to finish.