Amazon MLS-C01 dumps

Amazon MLS-C01 Dumps

AWS Certified Machine Learning - Specialty Dumps March 2023

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Amazon MLS-C01 Dumps

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Frequently Asked Questions


What is AWS Machine Learning Specialty confirmation?
AWS Machine Learning Specialty Certification looks at the capacity to execute, plan, and convey AI answers for business issues. In this applicant are required to perform information researcher job, based on which they are approved to tune, assemble, and convey the Machine learning model utilizing AWS cloud.
When do AWS Certifications lapses?
AWS Certifications are legitimate for a long time and after that, you have to refresh your confirmation.
What is the passing score for the AWS Certified Machine Learning Specialty test?
You have to score 750 out of 1000 to pass the AWS Certified Machine Learning Specialty test.
What are the prerequisites for AWS Machine Learning Specialty confirmation?
AWS Machine Learning Specialty confirmation requires comprehension in creating and running Machine learning outstanding tasks at hand with 1-2 years of experience on the AWS cloud. Decent information on Machine learning and profound learning structure with the capacity to communicate AI calculations.
What amount of time will you get during AWS Certified Machine Learning Specialty test?
In the AWS Certified Machine Learning Specialty test, you will get 170 minutes to finish the test.
What amount does the AWS Certified Machine Learning Specialty test cost?
This test will cost you $300 with extra assessments included.
Is there an approach to reschedule the AWS test?
Amazon Web Service (AWS) gives you the choice to reschedule your test 24 hours before the test arrangement. You have to go to your AWS affirmation record and snap-on Manage PSI tests, to reschedule or drop the test.
Is AWS the same as Azure?
1. Amazon Web Service (AWS) is presented by Amazon and Azure is a cloud administration by Microsoft. Both AWS and Azure are helping organizations to develop by offering types of assistance in different areas like system, stockpiling, and register.
2. AWS has basic stockpiling administration which is considered as the longest-running and Azure uses stockpiling square weave as capacity administrations.
3. AWS is useful for Iaas or enormous scope of administrations and for Paas or window mix Azure offers decent assistance.
Is the information on Linux required for AWS?
It isn't important to think about Linux in AWS. There is a need to think around one working framework whether it is Windows or Linux. Be that as it may, it very well may be a preferred position if you have an essential comprehension of Linux.

AWS MLS-C01 Sample Questions

Question # 1

A company is building a demand forecasting model based on machine learning (ML). In thedevelopment stage, an ML specialist uses an Amazon SageMaker notebook to performfeature engineering during work hours that consumes low amounts of CPU and memoryresources. A data engineer uses the same notebook to perform data preprocessing once aday on average that requires very high memory and completes in only 2 hours. The datapreprocessing is not configured to use GPU. All the processes are running well on anml.m5.4xlarge notebook instance.The company receives an AWS Budgets alert that the billing for this month exceeds theallocated budget.Which solution will result in the MOST cost savings?

A. Change the notebook instance type to a memory optimized instance with the samevCPU number as the ml.m5.4xlarge instance has. Stop the notebook when it is not in use.Run both data preprocessing and feature engineering development on that instance. 
B. Keep the notebook instance type and size the same. Stop the notebook when it is not inuse. Run data preprocessing on a P3 instance type with the same memory as theml.m5.4xlarge instance by using Amazon SageMaker Processing. 
C. Change the notebook instance type to a smaller general purpose instance. Stop thenotebook when it is not in use. Run data preprocessing on an ml.r5 instance with the samememory size as the ml.m5.4xlarge instance by using Amazon SageMaker Processing. 
D. Change the notebook instance type to a smaller general purpose instance. Stop thenotebook when it is not in use. Run data preprocessing on an R5 instance with the samememory size as the ml.m5.4xlarge instance by using the Reserved Instance option. 

ANSWER : B


Question # 2

A manufacturing company wants to use machine learning (ML) to automate quality controlin its facilities. The facilities are in remote locations and have limited internet connectivity.The company has 20 of training data that consists of labeled images of defective productparts. The training data is in the corporate on-premises data center.The company will use this data to train a model for real-time defect detection in new partsas the parts move on a conveyor belt in the facilities. The company needs a solution thatminimizes costs for compute infrastructure and that maximizes the scalability of resourcesfor training. The solution also must facilitate the company’s use of an ML model in the lowconnectivity environments.Which solution will meet these requirements?

A. Move the training data to an Amazon S3 bucket. Train and evaluate the model by usingAmazon SageMaker. Optimize the model by using SageMaker Neo. Deploy the model on aSageMaker hosting services endpoint. 
B. Train and evaluate the model on premises. Upload the model to an Amazon S3 bucket.Deploy the model on an Amazon SageMaker hosting services endpoint. 
C. Move the training data to an Amazon S3 bucket. Train and evaluate the model by usingAmazon SageMaker. Optimize the model by using SageMaker Neo. Set up an edge devicein the manufacturing facilities with AWS IoT Greengrass. Deploy the model on the edgedevice. 
D. Train the model on premises. Upload the model to an Amazon S3 bucket. Set up anedge device in the manufacturing facilities with AWS IoT Greengrass. Deploy the model onthe edge device. 

ANSWER : A


Question # 3

A company is building a predictive maintenance model based on machine learning (ML).The data is stored in a fully private Amazon S3 bucket that is encrypted at rest with AWSKey Management Service (AWS KMS) CMKs. An ML specialist must run datapreprocessing by using an Amazon SageMaker Processing job that is triggered from codein an Amazon SageMaker notebook. The job should read data from Amazon S3, process it,and upload it back to the same S3 bucket. The preprocessing code is stored in a containerimage in Amazon Elastic Container Registry (Amazon ECR). The ML specialist needs togrant permissions to ensure a smooth data preprocessing workflowWhich set of actions should the ML specialist take to meet these requirements?

A. Create an IAM role that has permissions to create Amazon SageMaker Processing jobs,S3 read and write access to the relevant S3 bucket, and appropriate KMS and ECRpermissions. Attach the role to the SageMaker notebook instance. Create an AmazonSageMaker Processing job from the notebook. 
B. Create an IAM role that has permissions to create Amazon SageMaker Processing jobs.Attach the role to the SageMaker notebook instance. Create an Amazon SageMakerProcessing job with an IAM role that has read and write permissions to the relevant S3bucket, and appropriate KMS and ECR permissions. 
C. Create an IAM role that has permissions to create Amazon SageMaker Processing jobsand to access Amazon ECR. Attach the role to the SageMaker notebook instance. Set upboth an S3 endpoint and a KMS endpoint in the default VPC. Create Amazon SageMakerProcessing jobs from the notebook. 
D. Create an IAM role that has permissions to create Amazon SageMaker Processing jobs.Attach the role to the SageMaker notebook instance. Set up an S3 endpoint in the defaultVPC. Create Amazon SageMaker Processing jobs with the access key and secret key ofthe IAM user with appropriate KMS and ECR permissions. 

ANSWER : D


Question # 4

A machine learning specialist is developing a proof of concept for government users whoseprimary concern is security. The specialist is using Amazon SageMaker to train aconvolutional neural network (CNN) model for a photo classifier application. The specialistwants to protect the data so that it cannot be accessed and transferred to a remote host bymalicious code accidentally installed on the training container.Which action will provide the MOST secure protection?

A. Remove Amazon S3 access permissions from the SageMaker execution role. 
B. Encrypt the weights of the CNN model. 
C. Encrypt the training and validation dataset. 
D. Enable network isolation for training jobs. 

ANSWER : D


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