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NEW QUESTION 27
A Machine Learning Specialist works for a credit card processing company and needs to predict which transactions may be fraudulent in near-real time. Specifically, the Specialist must train a model that returns the probability that a given transaction may fraudulent.
How should the Specialist frame this business problem?

A. Streaming classificationB. Regression classificationC. Binary classificationD. Multi-category classification

Answer: D

 

NEW QUESTION 28
A Machine Learning Specialist is working with a large company to leverage machine learning within its products. The company wants to group its customers into categories based on which customers will and will not churn within the next 6 months. The company has labeled the data available to the Specialist.
Which machine learning model type should the Specialist use to accomplish this task?

A. Linear regressionB. ClassificationC. ClusteringD. Reinforcement learning

Answer: B

Explanation:
The goal of classification is to determine to which class or category a data point (customer in our case) belongs to. For classification problems, data scientists would use historical data with predefined target variables AKA labels (churner/non-churner) - answers that need to be predicted - to train an algorithm. With classification, businesses can answer the following questions:
* Will this customer churn or not?
* Will a customer renew their subscription?
* Will a user downgrade a pricing plan?
* Are there any signs of unusual customer behavior?
Reference: https://www.kdnuggets.com/2019/05/churn-prediction-machine-learning.html

 

NEW QUESTION 29
A logistics company needs a forecast model to predict next month's inventory requirements for a single item in
10 warehouses. A machine learning specialist uses Amazon Forecast to develop a forecast model from 3 years of monthly data. There is no missing data. The specialist selects the DeepAR+ algorithm to train a predictor. The predictor means absolute percentage error (MAPE) is much larger than the MAPE produced by the current human forecasters.
Which changes to the CreatePredictor API call could improve the MAPE? (Choose two.)

A. Set PerformAutoML to true.B. Set ForecastFrequency to W for weekly.C. Set ForecastHorizon to 4.D. Set PerformHPO to true.E. Set FeaturizationMethodName to filling.

Answer: B,D

Explanation:
Explanation/Reference: https://docs.aws.amazon.com/forecast/latest/dg/forecast.dg.pdf

 

NEW QUESTION 30
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