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MLS-C01 Dumps With Exact Questions and Answers

Exact2pass Provides 100% Valid AWS Certified Machine Learning - Specialty MLS-C01 Exam dumps Questions and answers which can helps you to Pass Your Certification Exam in First Attempt.

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MLS-C01 Questions and Answers

Question # 1

A data scientist needs to identify fraudulent user accounts for a company's ecommerce platform. The company wants the ability to determine if a newly created account is associated with a previously known fraudulent user. The data scientist is using AWS Glue to cleanse the company's application logs during ingestion.

Which strategy will allow the data scientist to identify fraudulent accounts?


Execute the built-in FindDuplicates Amazon Athena query.


Create a FindMatches machine learning transform in AWS Glue.


Create an AWS Glue crawler to infer duplicate accounts in the source data.


Search for duplicate accounts in the AWS Glue Data Catalog.

Question # 2

A retail company uses a machine learning (ML) model for daily sales forecasting. The company’s brand manager reports that the model has provided inaccurate results for the past 3 weeks.

At the end of each day, an AWS Glue job consolidates the input data that is used for the forecasting with the actual daily sales data and the predictions of the model. The AWS Glue job stores the data in Amazon S3. The company’s ML team is using an Amazon SageMaker Studio notebook to gain an understanding about the source of the model's inaccuracies.

What should the ML team do on the SageMaker Studio notebook to visualize the model's degradation MOST accurately?


Create a histogram of the daily sales over the last 3 weeks. In addition, create a histogram of the daily sales from before that period.


Create a histogram of the model errors over the last 3 weeks. In addition, create a histogram of the model errors from before that period.


Create a line chart with the weekly mean absolute error (MAE) of the model.


Create a scatter plot of daily sales versus model error for the last 3 weeks. In addition, create a scatter plot of daily sales versus model error from before that period.

Question # 3

Amazon Connect has recently been tolled out across a company as a contact call center The solution has been configured to store voice call recordings on Amazon S3

The content of the voice calls are being analyzed for the incidents being discussed by the call operators Amazon Transcribe is being used to convert the audio to text, and the output is stored on Amazon S3

Which approach will provide the information required for further analysis?


Use Amazon Comprehend with the transcribed files to build the key topics


Use Amazon Translate with the transcribed files to train and build a model for the key topics


Use the AWS Deep Learning AMI with Gluon Semantic Segmentation on the transcribed files to train and build a model for the key topics


Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the transcribed files to generate a word embeddings dictionary for the key topics

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