AWS Certified Data Analytics Specialty 2021 - Hands-On! - [Exercise] Amazon Machine Learning - Part 2

The video tutorial covers the process of training and evaluating a regression model using Amazon Machine Learning. It explains the difference between numerical regression and classification problems, and highlights the importance of data cleaning to improve model accuracy. The tutorial also demonstrates real-time predictions and discusses the evaluation results, emphasizing the need for data preparation to achieve better outcomes.

What is the main challenge in predicting quantities based on past behavior?

• Limited data availability

• Wide range of quantities ordered

• Inaccurate data collection

• Complexity of algorithms

What type of problem is it when predicting a number with meaningful order?

• Multiclass classification

• Clustering

• Numerical regression

• Binary classification

Which classification problem involves choosing between more than two categories?

• Numerical regression

• Multiclass classification

• Hierarchical classification

• Binary classification

What was the model's quality score compared to the baseline?

• Significantly worse

• Much better

• Slightly better

• The same

What is a key step in preparing data for machine learning?

• Reducing data dimensions

• Cleaning data of outliers

• Increasing data size

• Randomizing data order

Why might some buyers purchase extremely large quantities?

• To test the system

• Due to data entry errors

• To resell or for institutional needs

• For personal use

What tool was used to predict order quantities in the example?

• Microsoft Azure ML

• Google Cloud ML

• Amazon ML

• IBM Watson