MLS-C01.pdf Demo Quiz

Question 1

[Modeling]
An agricultural company is interested in using machine learning to detect specific types of weeds in a
100-acre grassland field. Currently, the company uses tractor-mounted cameras to capture multiple
images of the field as 10 × 10 grids. The company also has a large training dataset that consists of
annotated images of popular weed classes like broadleaf and non-broadleaf docks.
The company wants to build a weed detection model that will detect specific types of weeds and the
location of each type within the field. Once the model is ready, it will be hosted on Amazon
SageMaker endpoints. The model will perform real-time inferencing using the images captured by
the cameras.
Which approach should a Machine Learning Specialist take to obtain accurate predictions?

Accepted Answer

Prepare the images in RecordIO format and upload them to Amazon S3. Use Amazon SageMaker
to train, test, and validate the model using an object-detection single-shot multibox detector (SSD)
algorithm.

Answer

Prepare the images in RecordIO format and upload them to Amazon S3. Use Amazon SageMaker
to train, test, and validate the model using an image classification algorithm to categorize images
into various weed classes.

Answer

Prepare the images in Apache Parquet format and upload them to Amazon S3. Use Amazon
SageMaker to train, test, and validate the model using an object-detection single-shot multibox
detector (SSD) algorithm.

Answer

Prepare the images in Apache Parquet format and upload them to Amazon S3. Use Amazon
SageMaker to train, test, and validate the model using an image classification algorithm to categorize
images into various weed classes.

Question 2

[Data Engineering]
A retail company is ingesting purchasing records from its network of 20,000 stores to Amazon S3 by
using Amazon Kinesis Data Firehose. The company uses a small, server-based application in each
store to send the data to AWS over the internet. The company uses this data to train a machine
learning model that is retrained each day. The company's data science team has identified existing
attributes on these records that could be combined to create an improved model.
Which change will create the required transformed records with the LEAST operational overhead?

Accepted Answer

Create an AWS Lambda function that can transform the incoming records. Enable data
transformation on the ingestion Kinesis Data Firehose delivery stream. Use the Lambda function as
the invocation target.

Answer

Deploy an Amazon EMR cluster that runs Apache Spark and includes the transformation logic. Use
Amazon EventBridge (Amazon CloudWatch Events) to schedule an AWS Lambda function to launch
the cluster each day and transform the records that accumulate in Amazon S3. Deliver the
transformed records to Amazon S3.

Answer

Deploy an Amazon S3 File Gateway in the stores. Update the in-store software to deliver data to
the S3 File Gateway. Use a scheduled daily AWS Glue job to transform the data that the S3 File
Gateway delivers to Amazon S3.

Answer

Launch a fleet of Amazon EC2 instances that include the transformation logic. Configure the EC2
instances with a daily cron job to transform the records that accumulate in Amazon S3. Deliver the
transformed records to Amazon S3.

Question 3

[Data Engineering]
A large JSON dataset for a project has been uploaded to a private Amazon S3 bucket The Machine
Learning Specialist wants to securely access and explore the data from an Amazon SageMaker
notebook instance A new VPC was created and assigned to the Specialist
How can the privacy and integrity of the data stored in Amazon S3 be maintained while granting
access to the Specialist for analysis?

Accepted Answer

Launch the SageMaker notebook instance within the VPC and create an S3 VPC endpoint for the
notebook to access the data Define a custom S3 bucket policy to only allow requests from your VPC
to access the S3 bucket

Answer

Launch the SageMaker notebook instance within the VPC with SageMaker-provided internet
access enabled Use an S3 ACL to open read privileges to the everyone group

Answer

Launch the SageMaker notebook instance within the VPC and create an S3 VPC endpoint for the
notebook to access the data Copy the JSON dataset from Amazon S3 into the ML storage volume on
the SageMaker notebook instance and work against the local dataset

Answer

Launch the SageMaker notebook instance within the VPC with SageMaker-provided internet
access enabled. Generate an S3 pre-signed URL for access to data in the bucket

Question 4

[Data Engineering]
A medical imaging company wants to train a computer vision model to detect areas of concern on
patients' CT scans. The company has a large collection of unlabeled CT scans that are linked to each
patient and stored in an Amazon S3 bucket. The scans must be accessible to authorized users only. A
machine learning engineer needs to build a labeling pipeline.
Which set of steps should the engineer take to build the labeling pipeline with the LEAST effort?

Accepted Answer

Create a private workforce and manifest file. Create a labeling job by using the built-in bounding
box task type in Amazon SageMaker Ground Truth. Write the labeling instructions.

Answer

Create a workforce with AWS Identity and Access Management (IAM). Build a labeling tool on
Amazon EC2 Queue images for labeling by using Amazon Simple Queue Service (Amazon SQS). Write
the labeling instructions.

Answer

Create an Amazon Mechanical Turk workforce and manifest file. Create a labeling job by using the
built-in image classification task type in Amazon SageMaker Ground Truth. Write the labeling
instructions.

Answer

Create a workforce with Amazon Cognito. Build a labeling web application with AWS Amplify.
Build a labeling workflow backend using AWS Lambda. Write the labeling instructions.

Question 5

[Data Engineering]
A machine learning specialist is preparing data for training on Amazon SageMaker. The specialist is
using one of the SageMaker built-in algorithms for the training. The dataset is stored in .CSV format
and is transformed into a numpy.array, which appears to be negatively affecting the speed of the
training.
What should the specialist do to optimize the data for training on SageMaker?

Accepted Answer

Transform the dataset into the RecordIO protobuf format.

Answer

Use the SageMaker batch transform feature to transform the training data into a DataFrame.

Answer

Use AWS Glue to compress the data into the Apache Parquet format.

Answer

Use the SageMaker hyperparameter optimization feature to automatically optimize the data.

Question 6

[Data Engineering]
A company wants to predict stock market price trends. The company stores stock market data each
business day in Amazon S3 in Apache Parquet format. The company stores 20 GB of data each day for
each stock code.
A data engineer must use Apache Spark to perform batch preprocessing data transformations quickly
so the company can complete prediction jobs before the stock market opens the next day. The
company plans to track more stock market codes and needs a way to scale the preprocessing data
transformations.
Which AWS service or feature will meet these requirements with the LEAST development effort over
time?

Accepted Answer

AWS Glue jobs

Answer

Amazon EMR cluster

Answer

Amazon Athena

Answer

AWS Lambda

Question 7

[Modeling]
A beauty supply store wants to understand some characteristics of visitors to the store. The store has
security video recordings from the past several years. The store wants to generate a report of hourly
visitors from the recordings. The report should group visitors by hair style and hair color.
Which solution will meet these requirements with the LEAST amount of effort?

Accepted Answer

Use a semantic segmentation algorithm to identify a visitor’s hair in video frames. Pass the
identified hair to an ResNet-50 algorithm to determine hair style and hair color.

Answer

Use an object detection algorithm to identify a visitor’s hair in video frames. Pass the identified
hair to an ResNet-50 algorithm to determine hair style and hair color.

Answer

Use an object detection algorithm to identify a visitor’s hair in video frames. Pass the identified
hair to an XGBoost algorithm to determine hair style and hair color.

Answer

Use a semantic segmentation algorithm to identify a visitor’s hair in video frames. Pass the
identified hair to an XGBoost algorithm to determine hair style and hair.

Question 8

[Data Engineering]
A Machine Learning Specialist is developing a daily ETL workflow containing multiple ETL jobs The
workflow consists of the following processes
* Start the workflow as soon as data is uploaded to Amazon S3
* When all the datasets are available in Amazon S3, start an ETL job to join the uploaded datasets
with multiple terabyte-sized datasets already stored in Amazon S3
* Store the results of joining datasets in Amazon S3
* If one of the jobs fails, send a notification to the Administrator
Which configuration will meet these requirements?

Accepted Answer

Use AWS Lambda to trigger an AWS Step Functions workflow to wait for dataset uploads to
complete in Amazon S3. Use AWS Glue to join the datasets Use an Amazon CloudWatch alarm to
send an SNS notification to the Administrator in the case of a failure

Answer

Develop the ETL workflow using AWS Lambda to start an Amazon SageMaker notebook instance
Use a lifecycle configuration script to join the datasets and persist the results in Amazon S3 Use an
Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure

Answer

Develop the ETL workflow using AWS Batch to trigger the start of ETL jobs when data is uploaded
to Amazon S3 Use AWS Glue to join the datasets in Amazon S3 Use an Amazon CloudWatch alarm to
send an SNS notification to the Administrator in the case of a failure

Answer

Use AWS Lambda to chain other Lambda functions to read and join the datasets in Amazon S3 as
soon as the data is uploaded to Amazon S3 Use an Amazon CloudWatch alarm to send an SNS
notification to the Administrator in the case of a failure

Question 9

[Modeling]
While working on a neural network project, a Machine Learning Specialist discovers thai some
features in the data have very high magnitude resulting in this data being weighted more in the cost
function What should the Specialist do to ensure better convergence during backpropagation?

Accepted Answer

Data normalization

Answer

Dimensionality reduction

Answer

Model regulanzation

Answer

Data augmentation for the minority class

Question 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?

Accepted Answer

Amazon Athena

Answer

Amazon Redshift Spectrum

Answer

AWS Glue

Answer

Amazon QuickSight

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