Amazon MLS-C01 AWS ML Specialty Exam Practice Test Instant Access

Question 1

[Data Engineering]

A data engineer is preparing a dataset that a retail company will use to predict the number of visitors to stores. The data engineer created an Amazon S3 bucket. The engineer subscribed the S3 bucket to an AWS Data Exchange data product for general economic indicators. The data engineer wants to join the economic indicator data to an existing table in Amazon Athena to merge with the business dat

a. All these transformations must finish running in 30-60 minutes.

Which solution will meet these requirements MOST cost-effectively?

AConfigure the AWS Data Exchange product as a producer for an Amazon Kinesis data stream. Use an Amazon Kinesis Data Firehose delivery stream to transfer the data to Amazon S3 Run an AWS Glue job that will merge the existing business data with the Athena table. Write the result set back to Amazon S3.

BUse an S3 event on the AWS Data Exchange S3 bucket to invoke an AWS Lambda function. Program the Lambda function to use Amazon SageMaker Data Wrangler to merge the existing business data with the Athena table. Write the result set back to Amazon S3.

CUse an S3 event on the AWS Data Exchange S3 bucket to invoke an AWS Lambda Function Program the Lambda function to run an AWS Glue job that will merge the existing business data with the Athena table Write the results back to Amazon S3.

DProvision an Amazon Redshift cluster. Subscribe to the AWS Data Exchange product and use the product to create an Amazon Redshift Table Merge the data in Amazon Redshift. Write the results back to Amazon S3.

Answer : B

Question 2

[Modeling]

A Machine Learning Specialist is working with a large company to leverage machine learning within its products. The company wants to group its customers into categories based on which customers will and will not churn within the next 6 months. The company has labeled the data available to the Specialist.

Which machine learning model type should the Specialist use to accomplish this task?

ALinear regression

BClassification

CClustering

DReinforcement learning

Answer : B

Question 3

[Data Engineering]

A company wants to predict the classification of documents that are created from an application. New documents are saved to an Amazon S3 bucket every 3 seconds. The company has developed three versions of a machine learning (ML) model within Amazon SageMaker to classify document text. The company wants to deploy these three versions to predict the classification of each document.

Which approach will meet these requirements with the LEAST operational overhead?

AConfigure an S3 event notification that invokes an AWS Lambda function when new documents are created. Configure the Lambda function to create three SageMaker batch transform jobs, one batch transform job for each model for each document.

BDeploy all the models to a single SageMaker endpoint. Treat each model as a production variant. Configure an S3 event notification that invokes an AWS Lambda function when new documents are created. Configure the Lambda function to call each production variant and return the results of each model.

CDeploy each model to its own SageMaker endpoint Configure an S3 event notification that invokes an AWS Lambda function when new documents are created. Configure the Lambda function to call each endpoint and return the results of each model.

DDeploy each model to its own SageMaker endpoint. Create three AWS Lambda functions. Configure each Lambda function to call a different endpoint and return the results. Configure three S3 event notifications to invoke the Lambda functions when new documents are created.

Answer : B

Question 4

[Modeling]

A company uses camera images of the tops of items displayed on store shelves to determine which items

were removed and which ones still remain. After several hours of data labeling, the company has a total of

1,000 hand-labeled images covering 10 distinct items. The training results were poor.

Which machine learning approach fulfills the company's long-term needs?

AConvert the images to grayscale and retrain the model

BReduce the number of distinct items from 10 to 2, build the model, and iterate

CAttach different colored labels to each item, take the images again, and build the model

DAugment training data for each item using image variants like inversions and translations, build the model, and iterate.

Answer : D

Question 5

[Exploratory Data Analysis]

A Machine Learning Specialist is building a convolutional neural network (CNN) that will classify 10 types of animals. The Specialist has built a series of layers in a neural network that will take an input image of an animal, pass it through a series of convolutional and pooling layers, and then finally pass it through a dense and fully connected layer with 10 nodes The Specialist would like to get an output from the neural network that is a probability distribution of how likely it is that the input image belongs to each of the 10 classes

Which function will produce the desired output?

ADropout

BSmooth L1 loss

CSoftmax

DRectified linear units (ReLU)

Answer : C

Question 6

[Modeling]

A Machine Learning Specialist is creating a new natural language processing application that processes a dataset comprised of 1 million sentences The aim is to then run Word2Vec to generate embeddings of the sentences and enable different types of predictions -

Here is an example from the dataset

"The quck BROWN FOX jumps over the lazy dog "

Which of the following are the operations the Specialist needs to perform to correctly sanitize and prepare the data in a repeatable manner? (Select THREE)

APerform part-of-speech tagging and keep the action verb and the nouns only

BNormalize all words by making the sentence lowercase

CRemove stop words using an English stopword dictionary.

DCorrect the typography on 'quck' to 'quick.'

EOne-hot encode all words in the sentence

FTokenize the sentence into words.

Answer : B, C, F

Question 7

[Modeling]

A Machine Learning Specialist trained a regression model, but the first iteration needs optimizing. The Specialist needs to understand whether the model is more frequently overestimating or underestimating the target.

What option can the Specialist use to determine whether it is overestimating or underestimating the target value?

ARoot Mean Square Error (RMSE)

BResidual plots

CArea under the curve

DConfusion matrix

Answer : B

Amazon AWS Certified Machine Learning - Specialty MLS-C01 AWS ML Specialty Exam Practice Test