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NEW QUESTION 33
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. Normal distribution
• B. Poisson distribution ,
• C. Uniform distribution
• D. Binomial distribution

Answer: B

NEW QUESTION 34
A company is using Amazon Polly to translate plaintext documents to speech for automated company announcements. However, company acronyms are being mispronounced in the current documents.
How should a Machine Learning Specialist address this issue for future documents?

• A. Use Amazon Lex to preprocess the text files for pronunciation
• B. Convert current documents to SSML with pronunciation tags.
• C. Output speech marks to guide in pronunciation.
• D. Create an appropriate pronunciation lexicon.

Answer: B

Explanation:
https://docs.aws.amazon.com/polly/latest/dg/ssml.html

NEW QUESTION 35
An agency collects census information within a country to determine healthcare and social program needs by province and city. The census form collects responses for approximately 500 questions from each citizen Which combination of algorithms would provide the appropriate insights? (Select TWO )

• A. The k-means algorithm g The Random Cut Forest (RCF) algorithm
• B. The Latent Dirichlet Allocation (LDA) algorithm
• C. The factorization machines (FM) algorithm
• D. The principal component analysis (PCA) algorithm

Answer: D

NEW QUESTION 36
A company that runs an online library is implementing a chatbot using Amazon Lex to provide book recommendations based on category. This intent is fulfilled by an AWS Lambda function that queries an Amazon DynamoDB table for a list of book titles, given a particular category. For testing, there are only three categories implemented as the custom slot types: "comedy," "adventure," and "documentary." A machine learning (ML) specialist notices that sometimes the request cannot be fulfilled because Amazon Lex cannot understand the category spoken by users with utterances such as "funny," "fun," and "humor." The ML specialist needs to fix the problem without changing the Lambda code or data in DynamoDB.
How should the ML specialist fix the problem?

• A. Add the unrecognized words as synonyms in the custom slot type.
• B. Use the AMAZON.SearchQuery built-in slot types for custom searches in the database.
• C. Add the unrecognized words in the enumeration values list as new values in the slot type.
• D. Create a new custom slot type, add the unrecognized words to this slot type as enumeration values, and use this slot type for the slot.

Answer: B

NEW QUESTION 37
A retail company intends to use machine learning to categorize new products A labeled dataset of current products was provided to the Data Science team The dataset includes 1 200 products The labeled dataset has 15 features for each product such as title dimensions, weight, and price Each product is labeled as belonging to one of six categories such as books, games, electronics, and movies.
Which model should be used for categorizing new products using the provided dataset for training?

• A. A regression forest where the number of trees is set equal to the number of product categories
• B. An XGBoost model where the objective parameter is set to multi: softmax
• C. A DeepAR forecasting model based on a recurrent neural network (RNN)
• D. A deep convolutional neural network (CNN) with a softmax activation function for the last layer

Answer: B

NEW QUESTION 38
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