Update AWS Certified Machine Learning - Specialty MLS-C01 Pdf

NEW QUESTION 1
A Machine Learning Specialist working for an online fashion company wants to build a data ingestion solution for the company's Amazon S3-based data lake.
The Specialist wants to create a set of ingestion mechanisms that will enable future capabilities comprised of:
• Real-time analytics
• Interactive analytics of historical data
• Clickstream analytics
• Product recommendations
Which services should the Specialist use?

• A. AWS Glue as the data dialog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for real-time data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations
• B. Amazon Athena as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for near-realtime data insights; Amazon Kinesis Data Firehose for clickstream analytics; AWS Glue to generate personalized product recommendations
• C. AWS Glue as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for historical data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations
• D. Amazon Athena as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for historical data insights; Amazon DynamoDB streams for clickstream analytics; AWS Glue to generate personalized product recommendations

Answer: A

NEW QUESTION 2
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?

• A. Dimensionality reduction
• B. Data normalization
• C. Model regulanzation
• D. Data augmentation for the minority class

Answer: D

NEW QUESTION 3
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

NEW QUESTION 4
A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket A Machine Learning Specialist wants to use SQL to run queries on this data. Which solution requires the LEAST effort to be able to query this data?

• A. Use AWS Data Pipeline to transform the data and Amazon RDS to run queries.
• B. Use AWS Glue to catalogue the data and Amazon Athena to run queries
• C. Use AWS Batch to run ETL on the data and Amazon Aurora to run the quenes
• D. Use AWS Lambda to transform the data and Amazon Kinesis Data Analytics to run queries

Answer: D

NEW QUESTION 5
A large mobile network operating company is building a machine learning model to predict customers who are likely to unsubscribe from the service. The company plans to offer an incentive for these customers as the cost of churn is far greater than the cost of the incentive.
The model produces the following confusion matrix after evaluating on a test dataset of 100 customers: Based on the model evaluation results, why is this a viable model for production?

• A. The model is 86% accurate and the cost incurred by the company as a result of false negatives is less than the false positives.
• B. The precision of the model is 86%, which is less than the accuracy of the model.
• C. The model is 86% accurate and the cost incurred by the company as a result of false positives is less than the false negatives.
• D. The precision of the model is 86%, which is greater than the accuracy of the model.

Answer: B

NEW QUESTION 6
A Marketing Manager at a pet insurance company plans to launch a targeted marketing campaign on social media to acquire new customers Currently, the company has the following data in Amazon Aurora
• Profiles for all past and existing customers
• Profiles for all past and existing insured pets
• Policy-level information
• Premiums received
• Claims paid
What steps should be taken to implement a machine learning model to identify potential new customers on social media?

• A. Use regression on customer profile data to understand key characteristics of consumer segments Find similar profiles on social media.
• B. Use clustering on customer profile data to understand key characteristics of consumer segments Find similar profiles on social media.
• C. Use a recommendation engine on customer profile data to understand key characteristics of consumer segment
• D. Find similar profiles on social media
• E. Use a decision tree classifier engine on customer profile data to understand key characteristics of consumer segment
• F. Find similar profiles on social media

Answer: C

NEW QUESTION 7
An Amazon SageMaker notebook instance is launched into Amazon VPC The SageMaker notebook references data contained in an Amazon S3 bucket in another account The bucket is encrypted using SSE-KMS The instance returns an access denied error when trying to access data in Amazon S3.
Which of the following are required to access the bucket and avoid the access denied error? (Select THREE )

• A. An AWS KMS key policy that allows access to the customer master key (CMK)
• B. A SageMaker notebook security group that allows access to Amazon S3
• C. An 1AM role that allows access to the specific S3 bucket
• D. A permissive S3 bucket policy
• E. An S3 bucket owner that matches the notebook owner
• F. A SegaMaker notebook subnet ACL that allow traffic to Amazon S3.

Answer: ACF

NEW QUESTION 8
A Data Science team within a large company uses Amazon SageMaker notebooks to access data stored in Amazon S3 buckets. The IT Security team is concerned that internet-enabled notebook instances create a security vulnerability where malicious code running on the instances could compromise data privacy. The company mandates that all instances stay within a secured VPC with no internet access, and data communication traffic must stay within the AWS network.
How should the Data Science team configure the notebook instance placement to meet these requirements?

• A. Associate the Amazon SageMaker notebook with a private subnet in a VP
• B. Place the Amazon SageMaker endpoint and S3 buckets within the same VPC.
• C. Associate the Amazon SageMaker notebook with a private subnet in a VP
• D. Use 1AM policies to grant access to Amazon S3 and Amazon SageMaker.
• E. Associate the Amazon SageMaker notebook with a private subnet in a VP
• F. Ensure the VPC has S3 VPC endpoints and Amazon SageMaker VPC endpoints attached to it.
• G. Associate the Amazon SageMaker notebook with a private subnet in a VP
• H. Ensure the VPC has a NAT gateway and an associated security group allowing only outbound connections to Amazon S3 and Amazon SageMaker

Answer: D

NEW QUESTION 9
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?

• 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.

Answer: C

NEW 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

NEW QUESTION 11
Example Corp has an annual sale event from October to December. The company has sequential sales data from the past 15 years and wants to use Amazon ML to predict the sales for this year's upcoming event. Which method should Example Corp use to split the data into a training dataset and evaluation dataset?

• A. Pre-split the data before uploading to Amazon S3
• B. Have Amazon ML split the data randomly.
• C. Have Amazon ML split the data sequentially.
• D. Perform custom cross-validation on the data

Answer: C

NEW QUESTION 12
A manufacturing company has a large set of labeled historical sales data The manufacturer would like to predict how many units of a particular part should be produced each quarter Which machine learning approach should be used to solve this problem?

• A. Logistic regression
• B. Random Cut Forest (RCF)
• C. Principal component analysis (PCA)
• D. Linear regression

Answer: B

NEW QUESTION 13
A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket. A Machine Learning Specialist wants to use SQL to run queries on this data.
Which solution requires the LEAST effort to be able to query this data?

• A. Use AWS Data Pipeline to transform the data and Amazon RDS to run queries.
• B. Use AWS Glue to catalogue the data and Amazon Athena to run queries.
• C. Use AWS Batch to run ETL on the data and Amazon Aurora to run the queries.
• D. Use AWS Lambda to transform the data and Amazon Kinesis Data Analytics to run queries.

Answer: B

NEW QUESTION 14
A Machine Learning Specialist is configuring Amazon SageMaker so multiple Data Scientists can access notebooks, train models, and deploy endpoints. To ensure the best operational performance, the Specialist needs to be able to track how often the Scientists are deploying models, GPU and CPU utilization on the deployed SageMaker endpoints, and all errors that are generated when an endpoint is invoked.
Which services are integrated with Amazon SageMaker to track this information? (Select TWO.)

• A. AWS CloudTrail
• B. AWS Health
• C. AWS Trusted Advisor
• D. Amazon CloudWatch
• E. AWS Config

Answer: AD

NEW QUESTION 15
An e-commerce company needs a customized training model to classify images of its shirts and pants products The company needs a proof of concept in 2 to 3 days with good accuracy Which compute choice should the Machine Learning Specialist select to train and achieve good accuracy on the model quickly?

• A. . m5 4xlarge (general purpose)
• B. r5.2xlarge (memory optimized)
• C. p3.2xlarge (GPU accelerated computing)
• D. p3 8xlarge (GPU accelerated computing)

Answer: C

NEW QUESTION 16
A Data Scientist needs to create a serverless ingestion and analytics solution for high-velocity, real-time streaming data.
The ingestion process must buffer and convert incoming records from JSON to a query-optimized, columnar format without data loss. The output datastore must be highly available, and Analysts must be able to run SQL queries against the data and connect to existing business intelligence dashboards.
Which solution should the Data Scientist build to satisfy the requirements?

• A. Create a schema in the AWS Glue Data Catalog of the incoming data forma
• B. Use an Amazon Kinesis Data Firehose delivery stream to stream the data and transform the data to Apache Parquet or ORC format using the AWS Glue Data Catalog before delivering to Amazon S3. Have the Analysts query the data directly from Amazon S3 using Amazon Athena, and connect to Bl tools using the Athena Java Database Connectivity (JDBC) connector.
• C. Write each JSON record to a staging location in Amazon S3. Use the S3 Put event to trigger an AWS Lambda function that transforms the data into Apache Parquet or ORC format and writes the data to a processed data location in Amazon S3. Have the Analysts query the data directly from Amazon S3 using Amazon Athena, and connect to Bl tools using the Athena Java Database Connectivity (JDBC) connector.
• D. Write each JSON record to a staging location in Amazon S3. Use the S3 Put event to trigger an AWS Lambda function that transforms the data into Apache Parquet or ORC format and inserts it into an Amazon RDS PostgreSQL databas
• E. Have the Analysts query and run dashboards from the RDS database.
• F. Use Amazon Kinesis Data Analytics to ingest the streaming data and perform real-time SQL queries to convert the records to Apache Parquet before delivering to Amazon S3. Have the Analysts query the data directly from Amazon S3 using Amazon Athena and connect to Bl tools using the Athena Java Database Connectivity (JDBC) connector.

Answer: A

NEW QUESTION 17
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: A

NEW QUESTION 18
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 sageMakerMode
• F. transform method to get inferences from the model hosted in SageMaker
• G. Convert the DataFrame object to a CSV file, and use the CSV file as input for obtaining inferences from SageMaker.

Answer: DEF

NEW QUESTION 19
The displayed graph is from a foresting model for testing a time series.

Considering the graph only, which conclusion should a Machine Learning Specialist make about the behavior of the model?

• A. The model predicts both the trend and the seasonality well.
• B. The model predicts the trend well, but not the seasonality.
• C. The model predicts the seasonality well, but not the trend.
• D. The model does not predict the trend or the seasonality well.

Answer: D

NEW QUESTION 20
A Machine Learning Specialist is designing a system for improving sales for a company. The objective is to use the large amount of information the company has on users' behavior and product preferences to predict which products users would like based on the users' similarity to other users.
What should the Specialist do to meet this objective?

• A. Build a content-based filtering recommendation engine with Apache Spark ML on Amazon EMR.
• B. Build a collaborative filtering recommendation engine with Apache Spark ML on Amazon EMR.
• C. Build a model-based filtering recommendation engine with Apache Spark ML on Amazon EMR.
• D. Build a combinative filtering recommendation engine with Apache Spark ML on Amazon EMR.

Answer: B

Explanation:
Many developers want to implement the famous Amazon model that was used to power the “People who bought this also bought these items” feature on Amazon.com. This model is based on a method called Collaborative Filtering. It takes items such as movies, books, and products that were rated highly by a set of users and recommending them to other users who also gave them high ratings. This method works well in domains where explicit ratings or implicit user actions can be gathered and analyzed.

NEW QUESTION 21
A Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training The Specialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs
What does the Specialist need to do1?

• A. Bundle the NVIDIA drivers with the Docker image
• B. Build the Docker container to be NVIDIA-Docker compatible
• C. Organize the Docker container's file structure to execute on GPU instances.
• D. Set the GPU flag in the Amazon SageMaker Create TrainingJob request body

Answer: A

NEW QUESTION 22
During mini-batch training of a neural network for a classification problem, a Data Scientist notices that training accuracy oscillates What is the MOST likely cause of this issue?

• A. The class distribution in the dataset is imbalanced
• B. Dataset shuffling is disabled
• C. The batch size is too big
• D. The learning rate is very high

Answer: D

NEW QUESTION 23
A gaming company has launched an online game where people can start playing for free but they need to pay if they choose to use certain features The company needs to build an automated system to predict whether or not a new user will become a paid user within 1 year The company has gathered a labeled dataset from 1 million users
The training dataset consists of 1.000 positive samples (from users who ended up paying within 1 year) and 999.1 negative samples (from users who did not use any paid features) Each data sample consists of 200 features including user age, device, location, and play patterns
Using this dataset for training, the Data Science team trained a random forest model that converged with over 99% accuracy on the training set However, the prediction results on a test dataset were not satisfactory.
Which of the following approaches should the Data Science team take to mitigate this issue? (Select TWO.)

• A. Add more deep trees to the random forest to enable the model to learn more features.
• B. indicate a copy of the samples in the test database in the training dataset
• C. Generate more positive samples by duplicating the positive samples and adding a small amount of noise to the duplicated data.
• D. Change the cost function so that false negatives have a higher impact on the cost value than false positives
• E. Change the cost function so that false positives have a higher impact on the cost value than false negatives

Answer: BD

NEW QUESTION 24
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?

• A. Linear regression
• B. Classification
• C. Clustering
• D. Reinforcement learning

Answer: B

Explanation:
The goal of classification is to determine to which class or category a data point (customer in our case) belongs to. For classification problems, data scientists would use historical data with predefined target variables AKA labels (churner/non-churner) – answers that need to be predicted – to train an algorithm. With classification,
businesses can answer the following questions:
Will this customer churn or not?
Will a customer renew their subscription?
Will a user downgrade a pricing plan?
Are there any signs of unusual customer behavior?

NEW QUESTION 25
A Machine Learning Specialist is using Amazon SageMaker to host a model for a highly available customer-facing application .
The Specialist has trained a new version of the model, validated it with historical data, and now wants to deploy it to production To limit any risk of a negative customer experience, the Specialist wants to be able to monitor the model and roll it back, if needed
What is the SIMPLEST approach with the LEAST risk to deploy the model and roll it back, if needed?

• A. Create a SageMaker endpoint and configuration for the new model versio
• B. Redirect production traffic to the new endpoint by updating the client configuratio
• C. Revert traffic to the last version if the model does not perform as expected.
• D. Create a SageMaker endpoint and configuration for the new model versio
• E. Redirect production traffic to the new endpoint by using a load balancer Revert traffic to the last version if the model does not perform as expected.
• F. Update the existing SageMaker endpoint to use a new configuration that is weighted to send 5% of the traffic to the new varian
• G. Revert traffic to the last version by resetting the weights if the model does not perform as expected.
• H. Update the existing SageMaker endpoint to use a new configuration that is weighted to send 100% of the traffic to the new variant Revert traffic to the last version by resetting the weights if the model does not perform as expected.

Answer: A

NEW QUESTION 26
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