Winter Special Limited Time 60% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: big60

Amazon Web Services Updated MLS-C01 Exam Questions and Answers by rueben

Page: 10 / 22

Amazon Web Services MLS-C01 Exam Overview :

Exam Name: AWS Certified Machine Learning - Specialty
Exam Code: MLS-C01 Dumps
Vendor: Amazon Web Services Certification: AWS Certified Specialty
Questions: 307 Q&A's Shared By: rueben
Question 40

A machine learning specialist is running an Amazon SageMaker endpoint using the built-in object detection algorithm on a P3 instance for real-time predictions in a company's production application. When evaluating the model's resource utilization, the specialist notices that the model is using only a fraction of the GPU.

Which architecture changes would ensure that provisioned resources are being utilized effectively?

Options:

A.

Redeploy the model as a batch transform job on an M5 instance.

B.

Redeploy the model on an M5 instance. Attach Amazon Elastic Inference to the instance.

C.

Redeploy the model on a P3dn instance.

D.

Deploy the model onto an Amazon Elastic Container Service (Amazon ECS) cluster using a P3 instance.

Discussion
Kylo
What makes Cramkey Dumps so reliable? Please guide.
Sami Aug 29, 2024
Well, for starters, they have a team of experts who are constantly updating their material to reflect the latest changes in the industry. Plus, they have a huge database of questions and answers, which makes it easy to study and prepare for the exam.
Madeleine
Passed my exam with my dream score…. Guys do give these dumps a try. They are authentic.
Ziggy Sep 3, 2024
That's really impressive. I think I might give Cramkey Dumps a try for my next certification exam.
Ilyas
Definitely. I felt much more confident and prepared because of the Cramkey Dumps. I was able to answer most of the questions with ease and I think that helped me to score well on the exam.
Saoirse Sep 25, 2024
That's amazing. I'm glad you found something that worked for you. Maybe I should try them out for my next exam.
Nylah
I've been looking for good study material for my upcoming certification exam. Need help.
Dolly Oct 3, 2024
Then you should definitely give Cramkey Dumps a try. They have a huge database of questions and answers, making it easy to study and prepare for the exam. And the best part is, you can be sure the information is accurate and relevant.
Laila
They're such a great resource for anyone who wants to improve their exam results. I used these dumps and passed my exam!! Happy customer, always prefer. Yes, same questions as above I know you guys are perfect.
Keira Aug 12, 2024
100% right….And they're so affordable too. It's amazing how much value you get for the price.
Question 41

A data scientist is training a large PyTorch model by using Amazon SageMaker. It takes 10 hours on average to train the model on GPU instances. The data scientist suspects that training is not converging and that

resource utilization is not optimal.

What should the data scientist do to identify and address training issues with the LEAST development effort?

Options:

A.

Use CPU utilization metrics that are captured in Amazon CloudWatch. Configure a CloudWatch alarm to stop the training job early if low CPU utilization occurs.

B.

Use high-resolution custom metrics that are captured in Amazon CloudWatch. Configure an AWS Lambda function to analyze the metrics and to stop the training job early if issues are detected.

C.

Use the SageMaker Debugger vanishing_gradient and LowGPUUtilization built-in rules to detect issues and to launch the StopTrainingJob action if issues are detected.

D.

Use the SageMaker Debugger confusion and feature_importance_overweight built-in rules to detect issues and to launch the StopTrainingJob action if issues are detected.

Discussion
Question 42

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?

Options:

A.

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

B.

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

C.

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

D.

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

Discussion
Question 43

A music streaming company is building a pipeline to extract features. The company wants to store the features for offline model training and online inference. The company wants to track feature history and to give the company's data science teams access to the features.

Which solution will meet these requirements with the MOST operational efficiency?

Options:

A.

Use Amazon SageMaker Feature Store to store features for model training and inference. Create an online store for online inference. Create an offline store for model training. Create an 1AM role for data scientists to access and search through feature groups.

B.

Use Amazon SageMaker Feature Store to store features for model training and inference. Create an online store for both online inference and model training. Create an 1AM role for data scientists to access and search through feature groups.

C.

Create one Amazon S3 bucket to store online inference features. Create a second S3 bucket to store offline model training features. Turn on

versioning for the S3 buckets and use tags to specify which tags are for online inference features and which are for offline model training features. Use Amazon Athena to query the S3 bucket for online inference. Connect the S3 bucket for offline model training to a SageMaker training job. Create

D.

Create two separate Amazon DynamoDB tables to store online inference features and offline model training features. Use time-based versioning on both tables. Query the DynamoDB table for online inference. Move the data from DynamoDB to Amazon S3 when a new SageMaker training job is launched. Create an 1AM policy that allows data scientists to access both tables.

Discussion
Page: 10 / 22
Title
Questions
Posted

MLS-C01
PDF

$42  $104.99

MLS-C01 Testing Engine

$50  $124.99

MLS-C01 PDF + Testing Engine

$66  $164.99