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Guide for AWS Certified Machine Learning - Specialty (MLS-C01)

Quiz AWS Certified Machine Learning - Specialty (MLS-C01)

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Quiz

1/10
[Data Engineering]
A machine learning specialist stores IoT soil sensor data in Amazon DynamoDB table and stores
weather event data as JSON files in Amazon S3. The dataset in DynamoDB is 10 GB in size and the
dataset in Amazon S3 is 5 GB in size. The specialist wants to train a model on this data to help predict
soil moisture levels as a function of weather events using Amazon SageMaker.
Which solution will accomplish the necessary transformation to train the Amazon SageMaker model
with the LEAST amount of administrative overhead?
Select the answer
1 correct answer
A.
Launch an Amazon EMR cluster. Create an Apache Hive external table for the DynamoDB table and S3 data. Join the Hive tables and write the results out to Amazon S3.
B.
Crawl the data using AWS Glue crawlers. Write an AWS Glue ETL job that merges the two tables and writes the output to an Amazon Redshift cluster.
C.
Enable Amazon DynamoDB Streams on the sensor table. Write an AWS Lambda function that consumes the stream and appends the results to the existing weather files in Amazon S3.
D.
Crawl the data using AWS Glue crawlers. Write an AWS Glue ETL job that merges the two tables and writes the output in CSV format to Amazon S3.

Quiz

2/10
[Data Engineering]
A Machine Learning Specialist is working for an online retailer that wants to run analytics on every
customer visit, processed through a machine learning pipeline. The data needs to be ingested by
Amazon Kinesis Data Streams at up to 100 transactions per second, and the JSON data blob is 100 KB
in size.
What is the MINIMUM number of shards in Kinesis Data Streams the Specialist should use to
successfully ingest this data?
Select the answer
1 correct answer
A.
1 shards
B.
10 shards
C.
100 shards
D.
1,000 shards

Quiz

3/10
[Modeling]
A Machine Learning Specialist receives customer data for an online shopping website. The data
includes demographics, past visits, and locality information. The Specialist must develop a machine
learning approach to identify the customer shopping patterns, preferences and trends to enhance
the website for better service and smart recommendations.
Which solution should the Specialist recommend?
Select the answer
1 correct answer
A.
Latent Dirichlet Allocation (LDA) for the given collection of discrete data to identify patterns in the customer database.
B.
A neural network with a minimum of three layers and random initial weights to identify patterns in the customer database
C.
Collaborative filtering based on user interactions and correlations to identify patterns in the customer database
D.
Random Cut Forest (RCF) over random subsamples to identify patterns in the customer database

Quiz

4/10
[Data Engineering]
A company has raw user and transaction data stored in AmazonS3 a MySQL database, and Amazon
RedShift A Data Scientist needs to perform an analysis by joining the three datasets from Amazon S3,
MySQL, and Amazon RedShift, and then calculating the average-of a few selected columns from the
joined data
Which AWS service should the Data Scientist use?
Select the answer
1 correct answer
A.
Amazon Athena
B.
Amazon Redshift Spectrum
C.
AWS Glue
D.
Amazon QuickSight

Quiz

5/10
[Modeling]
An online reseller has a large, multi-column dataset with one column missing 30% of its data A
Machine Learning Specialist believes that certain columns in the dataset could be used to reconstruct
the missing data.
Which reconstruction approach should the Specialist use to preserve the integrity of the dataset?
Select the answer
1 correct answer
A.
Listwise deletion
B.
Last observation carried forward
C.
Multiple imputation
D.
Mean substitution

Quiz

6/10
[Modeling]
A Machine Learning Specialist prepared the following graph displaying the results of k-means for k =


[1:10]

Certification Exam AWS Certified Machine Learning - Specialty (MLS-C01) Amazon Amazon-AWS-Certified-Machine-Learning-Specialty 1-3505651583

Considering the graph, what is a reasonable selection for the optimal choice of k?
Select the answer
1 correct answer
A.
1
B.
4
C.
7
D.
10

Quiz

7/10
[Exploratory Data Analysis]
A company is running a machine learning prediction service that generates 100 TB of predictions
every day A Machine Learning Specialist must generate a visualization of the daily precision-recall
curve from the predictions, and forward a read-only version to the Business team.
Which solution requires the LEAST coding effort?
Select the answer
1 correct answer
A.
Run a daily Amazon EMR workflow to generate precision-recall data, and save the results in Amazon S3 Give the Business team read-only access to S3
B.
Generate daily precision-recall data in Amazon QuickSight, and publish the results in a dashboard shared with the Business team
C.
Run a daily Amazon EMR workflow to generate precision-recall data, and save the results in Amazon S3 Visualize the arrays in Amazon QuickSight, and publish them in a dashboard shared with the Business team
D.
Generate daily precision-recall data in Amazon ES, and publish the results in a dashboard shared with the Business team.

Quiz

8/10
[Modeling]
A finance company needs to forecast the price of a commodity. The company has compiled a dataset
of historical daily prices. A data scientist must train various forecasting models on 80% of the dataset
and must validate the efficacy of those models on the remaining 20% of the dataset.
What should the data scientist split the dataset into a training dataset and a validation dataset to
compare model performance?
Select the answer
1 correct answer
A.
Pick a date so that 80% to the data points precede the date Assign that group of data points as the training dataset. Assign all the remaining data points to the validation dataset.
B.
Pick a date so that 80% of the data points occur after the date. Assign that group of data points as the training dataset. Assign all the remaining data points to the validation dataset.
C.
Starting from the earliest date in the dataset. pick eight data points for the training dataset and two data points for the validation dataset. Repeat this stratified sampling until no data points remain.
D.
Sample data points randomly without replacement so that 80% of the data points are in the training dataset. Assign all the remaining data points to the validation dataset.

Quiz

9/10
[Modeling]
A company distributes an online multiple-choice survey to several thousand people. Respondents to
the survey can select multiple options for each question.
A machine learning (ML) engineer needs to comprehensively represent every response from all
respondents in a dataset. The ML engineer will use the dataset to train a logistic regression model.
Which solution will meet these requirements?
Select the answer
1 correct answer
A.
Perform one-hot encoding on every possible option for each question of the survey.
B.
Perform binning on all the answers each respondent selected for each question.
C.
Use Amazon Mechanical Turk to create categorical labels for each set of possible responses.
D.
Use Amazon Textract to create numeric features for each set of possible responses.

Quiz

10/10
[Machine Learning Implementation and Operations]
A finance company has collected stock return data for 5.000 publicly traded companies. A financial
analyst has a dataset that contains 2.000 attributes for each company. The financial analyst wants to
use Amazon SageMaker to identify the top 15 attributes that are most valuable to predict future
stock returns.
Which solution will meet these requirements with the LEAST operational overhead?
Select the answer
1 correct answer
A.
Use the linear learner algorithm in SageMaker to train a linear regression model to predict the stock returns. Identify the most predictive features by ranking absolute coefficient values.
B.
Use random forest regression in SageMaker to train a model to predict the stock returns. Identify the most predictive features based on Gini importance scores.
C.
Use an Amazon SageMaker Data Wrangler quick model visualization to predict the stock returns. Identify the most predictive features based on the quick model's feature importance scores.
D.
Use Amazon SageMaker Autopilot to build a regression model to predict the stock returns. Identify the most predictive features based on an Amazon SageMaker Clarify report.
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  • Quiz name:AWS Certified Machine Learning - Specialty (MLS-C01)
  • Total number of questions:330
  • Number of questions for the test:50
  • Pass score:80%

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