AWS Certified Machine Learning – Specialty Set 4

Welcome to AWS Certified Machine Learning - Specialty Set 5.

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1. You are consulting for a mountain climbing gear manufacturer and have been asked to design a machine learning approach for predicting the strength of a new line of climbing ropes. Which approach might you choose?
2. Your company currently has a large on-prem Hadoop cluster that contains data you would like to use for a training job. Your cluster is equipped with Mahout, Flume, Hive, Spark, and Ganglia. How might you most efficiently use this data?
3. You have launched a training job but it fails after a few minutes. What is the first thing you should do for troubleshooting?
4. You are working on a model that tries to predict the future revenue of select companies based on 50 years of historic data from public financial filings. What might be a strategy to determine if the model is reasonably accurate?
5. We are running a training job over and over again using slightly different, very large datasets as an experiment. Training is taking a very long time with your I/O-bound training algorithm and you want to improve training performance. What might you consider? (Choose 2)
6. You have been provided with a cleansed CSV dataset you will be using for a linear regression model. Of these tasks, which might you do next? (Choose 2)
7. We are designing a binary classification model that tries to predict whether a customer is likely to respond to a direct mailing of our catalog. Because it is expensive to print and mail our catalog, we want to only send to customers where we have a high degree of certainty they will buy something. When considering if the customer will buy something, what outcome would we want to minimize in a confusion matrix?
8. Which of the following mean that our algorithm predicted false but the real outcome was true?
9. We are using a CSV dataset for unsupervised learning that does not include a target value. How should we indicate this for training data as it sits on S3?
10. You want to be sure to use the most stable version of a training container. How do you ensure this?
11. When you issue a CreateModel API call using a built-in algorithm, which of the following actions would be next?
12. We are using a k-fold method of cross-validation for our linear regression model. What outcome will indicate that our training data is not biased?


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