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Download AWS Certified Machine Learning - Specialty Exam Dumps

NEW QUESTION 46
Which of the following metrics should a Machine Learning Specialist generally use to compare/evaluate machine learning classification models against each other?

• A. Misclassification rate
• B. Mean absolute percentage error (MAPE)
• C. Recall
• D. Area Under the ROC Curve (AUC)

Answer: C

NEW QUESTION 47
A city wants to monitor its air quality to address the consequences of air pollution. A Machine Learning Specialist needs to forecast the air quality in parts per million of contaminates for the next 2 days in the city. As this is a prototype, only daily data from the last year is available.
Which model is MOST likely to provide the best results in Amazon SageMaker?

• A. Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year of data with a predictor_typeof classifier.
• B. Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the single time series consisting of the full year of data with a predictor_typeof regressor.
• C. Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year of data with a predictor_typeof regressor.
• D. Use Amazon SageMaker Random Cut Forest (RCF) on the single time series consisting of the full year of data.

Answer: C

Explanation:
Explanation/Reference: https://aws.amazon.com/blogs/machine-learning/build-a-model-to-predict-the-impact-of-weather- on-urban-air-quality-using-amazon-sagemaker/?ref=Welcome.AI

NEW QUESTION 48
A Machine Learning Specialist deployed a model that provides product recommendations on a company's website. Initially, the model was performing very well and resulted in customers buying more products on average. However, within the past few months, the Specialist has noticed that the effect of product recommendations has diminished and customers are starting to return to their original habits of spending less. The Specialist is unsure of what happened, as the model has not changed from its initial deployment over a year ago.
Which method should the Specialist try to improve model performance?

• A. The model's hyperparameters should be periodically updated to prevent drift.
• B. The model should be periodically retrained using the original training data plus new data as product inventory changes.
• C. The model needs to be completely re-engineered because it is unable to handle product inventory changes.
• D. The model should be periodically retrained from scratch using the original data while adding a regularization term to handle product inventory changes

Answer: B

NEW QUESTION 49
A Data Scientist needs to analyze employment data. The dataset contains approximately 10 million observations on people across 10 different features. During the preliminary analysis, the Data Scientist notices that income and age distributions are not normal. While income levels shows a right skew as expected, with fewer individuals having a higher income, the age distribution also show a right skew, with fewer older individuals participating in the workforce.
Which feature transformations can the Data Scientist apply to fix the incorrectly skewed data? (Choose two.)

• A. Logarithmic transformation
• B. One hot encoding
• C. High-degree polynomial transformation
• D. Cross-validation
• E. Numerical value binning

Answer: D,E

NEW QUESTION 50
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