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AWS Certified Machine Learning - Specialty
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Question #:1
IT leadership wants Jo transition a company's existing machine learning data storage environment to AWS as a
temporary ad hoc solution The company currently uses a custom software process that heavily leverages SOL
as a query language and exclusively stores generated csv documents for machine learning
The ideal state for the company would be a solution that allows it to continue to use the current workforce of
SQL experts The solution must also support the storage of csv and JSON files, and be able to query over
semi-structured data The following are high priorities for the company:
• Solution simplicity
• Fast development time
• Low cost
• High flexibility
What technologies meet the company's requirements?
A.  Amazon S3 and Amazon Athena
B.  Amazon Redshift and AWS Glue
C.  Amazon DynamoDB and DynamoDB Accelerator (DAX)
D.  Amazon RDS and Amazon ES
Answer: B
Question #:2
A Data Scientist wants to gain real-time insights into a data stream of GZIP files. Which solution would allow
the use of SQL to query the stream with the LEAST latency?
A.  Amazon Kinesis Data Analytics with an AWS Lambda function to transform the data.
B.  AWS Glue with a custom ETL script to transform the data.
C.  An Amazon Kinesis Client Library to transform the data and save it to an Amazon ES cluster.
D.  Amazon Kinesis Data Firehose to transform the data and put it into an Amazon S3 bucket.
Answer: D
Question #:3
A Machine Learning Specialist is using Apache Spark for pre-processing training data As part of the Spark
pipeline, the Specialist wants to use Amazon SageMaker for training a model and hosting it Which of the
following would the Specialist do to integrate the Spark application with SageMaker? (Select THREE )
A.  Download the AWS SDK for the Spark environment
B.  Install the SageMaker Spark library in the Spark environment.
C.  Use the appropriate estimator from the SageMaker Spark Library to train a model.
D.  Compress the training data into a ZIP file and upload it to a pre-defined Amazon S3 bucket.
E.  Use the sageMakerModel. transform method to get inferences from the model hosted in SageMaker
F.  Convert the DataFrame object to a CSV file, and use the CSV file as input for obtaining inferences from
SageMaker.
Answer: D E F
Question #:4
A Machine Learning Specialist prepared the following graph displaying the results of k-means for k = [1:10]
Considering the graph, what is a reasonable selection for the optimal choice of k?
A.  1
B.  4
C.  7
D.  10
Answer: C
Question #:5
A Machine Learning team uses Amazon SageMaker to train an Apache MXNet handwritten digit classifier
model using a research dataset. The team wants to receive a notification when the model is overfitting.
Auditors want to view the Amazon SageMaker log activity report to ensure there are no unauthorized API
calls.
What should the Machine Learning team do to address the requirements with the least amount of code and
fewest steps?
A.  Implement an AWS Lambda function to long Amazon SageMaker API calls to Amazon S3. Add code to
push a custom metric to Amazon CloudWatch. Create an alarm in CloudWatch with Amazon SNS to
receive a notification when the model is overfitting.
B.  Use AWS CloudTrail to log Amazon SageMaker API calls to Amazon S3. Add code to push a custom
metric to Amazon CloudWatch. Create an alarm in CloudWatch with Amazon SNS to receive a
notification when the model is overfitting.
C.  Implement an AWS Lambda function to log Amazon SageMaker API calls to AWS CloudTrail. Add
code to push a custom metric to Amazon CloudWatch. Create an alarm in CloudWatch with Amazon
SNS to receive a notification when the model is overfitting.
D.  Use AWS CloudTrail to log Amazon SageMaker API calls to Amazon S3. Set up Amazon SNS to
receive a notification when the model is overfitting.
Answer: D
Question #:6
A Machine Learning Specialist is building a logistic regression model that will predict whether or not a person
will order a pizza. The Specialist is trying to build the optimal model with an ideal classification threshold.
What model evaluation technique should the Specialist use to understand how different classification
thresholds will impact the model's performance?
A.  Receiver operating characteristic (ROC) curve
B.  Misclassification rate
C.  Root Mean Square Error (RM&)
D.  L1 norm
Answer: C
Question #:7
A Machine Learning Specialist is configuring automatic model tuning in Amazon SageMaker
When using the hyperparameter optimization feature, which of the following guidelines should be followed to
improve optimization?
Choose the maximum number of hyperparameters supported by
A.  Amazon SageMaker to search the largest number of combinations possible
B.  Specify a very large hyperparameter range to allow Amazon SageMaker to cover every possible value.
C.  Use log-scaled hyperparameters to allow the hyperparameter space to be searched as quickly as possible
D.  Execute only one hyperparameter tuning job at a time and improve tuning through successive rounds of
experiments
Answer: C
Question #:8
A Machine Learning Specialist was given a dataset consisting of unlabeled data The Specialist must create a
model that can help the team classify the data into different buckets What model should be used to complete
this work?
A.  K-means clustering
B.  Random Cut Forest (RCF)
C.  XGBoost
D.  BlazingText
Answer: A
Question #:9
Which of the following metrics should a Machine Learning Specialist generally use to compare/evaluate
machine learning classification models against each other?
A.  Recall
B.  Misclassification rate
C.  Mean absolute percentage error (MAPE)
D.  Area Under the ROC Curve (AUC)
Answer: D
Question #:10
A Machine Learning Specialist works for a credit card processing company and needs to predict which
transactions may be fraudulent in near-real time. Specifically, the Specialist must train a model that returns the
probability that a given transaction may be fraudulent
How should the Specialist frame this business problem'?
A.  Streaming classification
B.  Binary classification
C.  Multi-category classification
D.  Regression classification
Answer: A