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Amazon AWS Certified Machine Learning - Specialty Sample Questions (Q87-Q92):
NEW QUESTION # 87
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 dat a. 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.)
Answer: A,D
NEW QUESTION # 88
A financial services company is building a robust serverless data lake on Amazon S3. The data lake should be flexible and meet the following requirements:
* Support querying old and new data on Amazon S3 through Amazon Athena and Amazon Redshift Spectrum.
* Support event-driven ETL pipelines.
* Provide a quick and easy way to understand metadata.
Which approach meets trfese requirements?
Answer: B
Explanation:
To build a robust serverless data lake on Amazon S3 that meets the requirements, the financial services company should use the following AWS services:
AWS Glue crawler: This is a service that connects to a data store, progresses through a prioritized list of classifiers to determine the schema for the data, and then creates metadata tables in the AWS Glue Data Catalog1. The company can use an AWS Glue crawler to crawl the S3 data and infer the schema, format, and partition structure of the data. The crawler can also detect schema changes and update the metadata tables accordingly. This enables the company to support querying old and new data on Amazon S3 through Amazon Athena and Amazon Redshift Spectrum, which are serverless interactive query services that use the AWS Glue Data Catalog as a central location for storing and retrieving table metadata23.
AWS Lambda function: This is a service that lets you run code without provisioning or managing servers. You pay only for the compute time you consume - there is no charge when your code is not running. You can also use AWS Lambda to create event-driven ETL pipelines, by triggering other AWS services based on events such as object creation or deletion in S3 buckets4. The company can use an AWS Lambda function to trigger an AWS Glue ETL job, which is a serverless way to extract, transform, and load data for analytics. The AWS Glue ETL job can perform various data processing tasks, such as converting data formats, filtering, aggregating, joining, and more.
AWS Glue Data Catalog: This is a managed service that acts as a central metadata repository for data assets across AWS and on-premises data sources. The AWS Glue Data Catalog provides a uniform repository where disparate systems can store and find metadata to keep track of data in data silos, and use that metadata to query and transform the data. The company can use the AWS Glue Data Catalog to search and discover metadata, such as table definitions, schemas, and partitions. The AWS Glue Data Catalog also integrates with Amazon Athena, Amazon Redshift Spectrum, Amazon EMR, and AWS Glue ETL jobs, providing a consistent view of the data across different query and analysis services.
References:
1: What Is a Crawler? - AWS Glue
2: What Is Amazon Athena? - Amazon Athena
3: Amazon Redshift Spectrum - Amazon Redshift
4: What is AWS Lambda? - AWS Lambda
5: AWS Glue ETL Jobs - AWS Glue
6: What Is the AWS Glue Data Catalog? - AWS Glue
NEW QUESTION # 89
A Machine Learning Specialist is building a supervised model that will evaluate customers' satisfaction with their mobile phone service based on recent usage The model's output should infer whether or not a customer is likely to switch to a competitor in the next 30 days Which of the following modeling techniques should the Specialist use1?
Answer: B
Explanation:
The modeling technique that the Machine Learning Specialist should use is binary classification. Binary classification is a type of supervised learning that predicts whether an input belongs to one of two possible classes. In this case, the input is the customer's recent usage data and the output is whether or not the customer is likely to switch to a competitor in the next 30 days. This is a binary outcome, either yes or no, so binary classification is suitable for this problem. The other options are not appropriate for this problem. Time- series prediction is a type of supervised learning that forecasts future values based on past and present data.
Anomaly detection is a type of unsupervised learning that identifies outliers or abnormal patterns in the data.
Regression is a type of supervised learning that estimates a continuous numerical value based on the input features. References: Binary Classification, Time Series Prediction, Anomaly Detection, Regression
NEW QUESTION # 90
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?
Answer: D
NEW QUESTION # 91
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?
Answer: A
Explanation:
A pronunciation lexicon is a file that defines how words or phrases should be pronounced by Amazon Polly.
A lexicon can help customize the speech output for words that are uncommon, foreign, or have multiple pronunciations. A lexicon must conform to the Pronunciation Lexicon Specification (PLS) standard and can be stored in an AWS region using the Amazon Polly API. To use a lexicon for synthesizing speech, the lexicon name must be specified in the <speak> SSML tag. For example, the following lexicon defines how to pronounce the acronym W3C:
<lexicon
version="1.0" xmlns="http://www.w3.org/2005/01/pronunciation-lexicon" alphabet="ipa" xml:lang="en-US"
> <lexeme> <grapheme>W3C</grapheme> <alias>World Wide Web Consortium</alias> </lexeme> <
/lexicon>
To use this lexicon, the text input must include the following SSML tag:
<speak
version="1.1" xmlns="http://www.w3.org/2001/10/synthesis" xml:lang="en-US"
> <voice name="Joanna"> <lexicon name="w3c_lexicon"/> The <say-as interpret-as="characters">W3C<
/say-as> is an international community that develops open standards to ensure the long-term growth of the Web. </voice> </speak> References:
* Customize pronunciation using lexicons in Amazon Polly: A blog post that explains how to use lexicons for creating custom pronunciations.
* Managing Lexicons: A documentation page that describes how to store and retrieve lexicons using the Amazon Polly API.
NEW QUESTION # 92
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