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 challenges are associated with predicting quantities based on past behavior?

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Explain the difference between numerical regression and classification problems.

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What is the significance of the evaluation result in the context of the regression model?

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What were the actual and predicted values in the example discussed, and what does this indicate?

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Discuss the implications of having outliers in the dataset.

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Why is cleaning data important before feeding it into a machine learning algorithm?

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What steps can be taken to improve the performance of a regression model?

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