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Download AWS Certified Machine Learning – Specialty Exam Dumps
NEW QUESTION 25
A Machine Learning Specialist is given a structured dataset on the shopping habits of a company’s customer base. The dataset contains thousands of columns of data and hundreds of numerical columns for each customer. The Specialist wants to identify whether there are natural groupings for these columns across all customers and visualize the results as quickly as possible.
What approach should the Specialist take to accomplish these tasks?
- A. Run k-means using the Euclidean distance measure for different values of k and create an elbow plot.
- B. Embed the numerical features using the t-distributed stochastic neighbor embedding (t-SNE) algorithm and create a line graph.
- C. Embed the numerical features using the t-distributed stochastic neighbor embedding (t-SNE) algorithm and create a scatter plot.
- D. Run k-means using the Euclidean distance measure for different values of k and create box plots for each numerical column within each cluster.
Answer: A
NEW QUESTION 26
For the given confusion matrix, what is the recall and precision of the model?
- A. Recall = 0.92 Precision = 0.84
- B. Recall = 0.84 Precision = 0.8
- C. Recall = 0.92 Precision = 0.8
- D. Recall = 0.8 Precision = 0.92
Answer: A
NEW QUESTION 27
A large mobile network operating company is building a machine learning model to predict customers who are likely to unsubscribe from the service. The company plans to offer an incentive for these customers as the cost of churn is far greater than the cost of the incentive.
The model produces the following confusion matrix after evaluating on a test dataset of 100 customers:
Based on the model evaluation results, why is this a viable model for production?
- A. The model is 86% accurate and the cost incurred by the company as a result of false positives is less than the false negatives.
- B. The precision of the model is 86%, which is greater than the accuracy of the model.
- C. The precision of the model is 86%, which is less than the accuracy of the model.
- D. The model is 86% accurate and the cost incurred by the company as a result of false negatives is less than the false positives.
Answer: C
NEW QUESTION 28
A Machine Learning Specialist is implementing a full Bayesian network on a dataset that describes public transit in New York City. One of the random variables is discrete, and represents the number of minutes New Yorkers wait for a bus given that the buses cycle every 10 minutes, with a mean of 3 minutes.
Which prior probability distribution should the ML Specialist use for this variable?
- A. Uniform distribution
- B. Poisson distribution
- C. Binomial distribution
- D. Normal distribution
Answer: B
Explanation:
The Poisson distribution is used to model the number of events occurring within a given time interval.
NEW QUESTION 29
A retail company is using Amazon Personalize to provide personalized product recommendations for its customers during a marketing campaign. The company sees a significant increase in sales of recommended items to existing customers immediately after deploying a new solution version, but these sales decrease a short time after deployment. Only historical data from before the marketing campaign is available for training.
How should a data scientist adjust the solution?
- A. Use the event tracker in Amazon Personalize to include real-time user interactions.
- B. Add user metadata and use the HRNN-Metadata recipe in Amazon Personalize.
- C. Implement a new solution using the built-in factorization machines (FM) algorithm in Amazon SageMaker.
- D. Add event type and event value fields to the interactions dataset in Amazon Personalize.
Answer: A
NEW QUESTION 30
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