CERTIFICATION AWS-CERTIFIED-MACHINE-LEARNING-SPECIALTY TEST ANSWERS - EXAM AWS-CERTIFIED-MACHINE-LEARNING-SPECIALTY STUDY SOLUTIONS

Certification AWS-Certified-Machine-Learning-Specialty Test Answers - Exam AWS-Certified-Machine-Learning-Specialty Study Solutions

Certification AWS-Certified-Machine-Learning-Specialty Test Answers - Exam AWS-Certified-Machine-Learning-Specialty Study Solutions

Blog Article

Tags: Certification AWS-Certified-Machine-Learning-Specialty Test Answers, Exam AWS-Certified-Machine-Learning-Specialty Study Solutions, AWS-Certified-Machine-Learning-Specialty Free Braindumps, Simulation AWS-Certified-Machine-Learning-Specialty Questions, Latest Real AWS-Certified-Machine-Learning-Specialty Exam

2025 Latest SurePassExams AWS-Certified-Machine-Learning-Specialty PDF Dumps and AWS-Certified-Machine-Learning-Specialty Exam Engine Free Share: https://drive.google.com/open?id=1q7Ya1ef2wKV3SUGc4-cHqcGP2UE4uExl

If you have decided to participate in the Amazon AWS-Certified-Machine-Learning-Specialty exam, SurePassExams is here. We can help you achieve your goals. We know that you need to pass your Amazon AWS-Certified-Machine-Learning-Specialty Exam, we promise that provide high quality exam materials for you, Which can help you through Amazon AWS-Certified-Machine-Learning-Specialty exam.

Our AWS-Certified-Machine-Learning-Specialty study materials are very popular in the international market and enjoy wide praise by the people in and outside the circle. We have shaped our AWS-Certified-Machine-Learning-Specialty exam questions into a famous and top-ranking brand and we enjoy well-deserved reputation among the clients. Our AWS-Certified-Machine-Learning-Specialty learning guide boosts many outstanding and superior advantages which other same kinds of exam materials don’t have. And we are very reliable in every aspect no matter on the quality or the according service.

>> Certification AWS-Certified-Machine-Learning-Specialty Test Answers <<

Exam AWS-Certified-Machine-Learning-Specialty Study Solutions, AWS-Certified-Machine-Learning-Specialty Free Braindumps

In rare cases, if you fail to pass the AWS Certified Machine Learning - Specialty AWS-Certified-Machine-Learning-Specialty exam despite using AWS Certified Machine Learning - Specialty exam dumps we will return your whole payment without any deduction. Take the best decision of your professional career and start exam preparation with AWS Certified Machine Learning - Specialty exam practice questions and become a certified AWS Certified Machine Learning - Specialty AWS-Certified-Machine-Learning-Specialty expert.

To take the Amazon MLS-C01 exam, candidates must first pass the AWS Certified Cloud Practitioner or AWS Certified Solutions Architect Associate exam. AWS-Certified-Machine-Learning-Specialty Exam consists of 65 multiple-choice and multiple-response questions and must be completed in 180 minutes. AWS-Certified-Machine-Learning-Specialty exam is available in several languages, including English, Japanese, Korean, and Simplified Chinese. Upon passing the exam, candidates will receive an AWS Certified Machine Learning – Specialty certification, which is valid for three years. AWS Certified Machine Learning - Specialty certification demonstrates to employers and clients that the individual has the skills and knowledge needed to design, implement, and maintain machine learning solutions on the AWS platform.

To be eligible for the Amazon MLS-C01 certification exam, candidates must have a minimum of one year of experience in designing and implementing machine learning solutions using AWS services. They should also have experience in data pre-processing, feature engineering, model selection, and model evaluation. Additionally, candidates should have knowledge of programming languages such as Python, R, and Java.

Amazon AWS Certified Machine Learning - Specialty Sample Questions (Q180-Q185):

NEW QUESTION # 180
An insurance company developed a new experimental machine learning (ML) model to replace an existing model that is in production. The company must validate the quality of predictions from the new experimental model in a production environment before the company uses the new experimental model to serve general user requests.
Which one model can serve user requests at a time. The company must measure the performance of the new experimental model without affecting the current live traffic Which solution will meet these requirements?

  • A. A/B testing
  • B. Shadow deployment
  • C. Blue/green deployment
  • D. Canary release

Answer: B

Explanation:
The best solution for this scenario is to use shadow deployment, which is a technique that allows the company to run the new experimental model in parallel with the existing model, without exposing it to the end users. In shadow deployment, the company can route the same user requests to both models, but only return the responses from the existing model to the users. The responses from the new experimental model are logged and analyzed for quality and performance metrics, such as accuracy, latency, and resource consumption12.
This way, the company can validate the new experimental model in a production environment, without affecting the current live traffic or user experience.
The other solutions are not suitable, because they have the following drawbacks:
* A: A/B testing is a technique that involves splitting the user traffic between two or more models, and comparing their outcomes based on predefined metrics. However, this technique exposes the new experimental model to a portion of the end users, which might affect their experience if the model is not reliable or consistent with the existing model3.
* B: Canary release is a technique that involves gradually rolling out the new experimental model to a small subset of users, and monitoring its performance and feedback. However, this technique also exposes the new experimental model to some end users, and requires careful selection and segmentation of the user groups4.
* D: Blue/green deployment is a technique that involves switching the user traffic from the existing model (blue) to the new experimental model (green) at once, after testing and verifying the new model in a separate environment. However, this technique does not allow the company to validate the new experimental model in a production environment, and might cause service disruption or inconsistency if the new model is not compatible or stable5.
References:
* 1: Shadow Deployment: A Safe Way to Test in Production | LaunchDarkly Blog
* 2: Shadow Deployment: A Safe Way to Test in Production | LaunchDarkly Blog
* 3: A/B Testing for Machine Learning Models | AWS Machine Learning Blog
* 4: Canary Releases for Machine Learning Models | AWS Machine Learning Blog
* 5: Blue-Green Deployments for Machine Learning Models | AWS Machine Learning Blog


NEW QUESTION # 181
A Machine Learning Specialist wants to determine the appropriate SageMaker Variant Invocations Per Instance setting for an endpoint automatic scaling configuration. The Specialist has performed a load test on a single instance and determined that peak requests per second (RPS) without service degradation is about 20 RPS As this is the first deployment, the Specialist intends to set the invocation safety factor to 0 5 Based on the stated parameters and given that the invocations per instance setting is measured on a per-minute basis, what should the Specialist set as the sageMaker variant invocations Per instance setting?

  • A. 0
  • B. 1
  • C. 2,400
  • D. 2

Answer: A

Explanation:
Explanation
The SageMaker Variant Invocations Per Instance setting is the target value for the average number of invocations per instance per minute for the model variant. It is used by the automatic scaling policy to add or remove instances to keep the metric close to the specified value. To determine this value, the following equation can be used in combination with load testing:
SageMakerVariantInvocationsPerInstance = (MAX_RPS * SAFETY_FACTOR) * 60 Where MAX_RPS is the maximum requests per second that the model variant can handle without service degradation, SAFETY_FACTOR is a factor that ensures that the clients do not exceed the maximum RPS, and
60 is the conversion factor from seconds to minutes. In this case, the given parameters are:
MAX_RPS = 20 SAFETY_FACTOR = 0.5
Plugging these values into the equation, we get:
SageMakerVariantInvocationsPerInstance = (20 * 0.5) * 60 SageMakerVariantInvocationsPerInstance = 600 Therefore, the Specialist should set the SageMaker Variant Invocations Per Instance setting to 600.
References:
Load testing your auto scaling configuration - Amazon SageMaker
Configure model auto scaling with the console - Amazon SageMaker


NEW QUESTION # 182
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 data. All these transformations must finish running in 30-60 minutes.
Which solution will meet these requirements MOST cost-effectively?

  • A. Configure 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.
  • B. Use 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.
  • C. Use 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.
  • D. Provision 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: C

Explanation:
Explanation
The most cost-effective solution is to use an S3 event to trigger a Lambda function that uses SageMaker Data Wrangler to merge the data. This solution avoids the need to provision and manage any additional resources, such as Kinesis streams, Firehose delivery streams, Glue jobs, or Redshift clusters. SageMaker Data Wrangler provides a visual interface to import, prepare, transform, and analyze data from various sources, including AWS Data Exchange products. It can also export the data preparation workflow to a Python script that can be executed by a Lambda function. This solution can meet the time requirement of 30-60 minutes, depending on the size and complexity of the data.
References:
Using Amazon S3 Event Notifications
Prepare ML Data with Amazon SageMaker Data Wrangler
AWS Lambda Function


NEW QUESTION # 183
A company will use Amazon SageMaker to train and host a machine learning (ML) model for a marketing campaign. The majority of data is sensitive customer data. The data must be encrypted at rest. The company wants AWS to maintain the root of trust for the master keys and wants encryption key usage to be logged.
Which implementation will meet these requirements?

  • A. Use customer managed keys in AWS Key Management Service (AWS KMS) to encrypt the ML data volumes, and to encrypt the model artifacts and data in Amazon S3.
  • B. Use AWS Security Token Service (AWS STS) to create temporary tokens to encrypt the ML storage volumes, and to encrypt the model artifacts and data in Amazon S3.
  • C. Use SageMaker built-in transient keys to encrypt the ML data volumes. Enable default encryption for new Amazon Elastic Block Store (Amazon EBS) volumes.
  • D. Use encryption keys that are stored in AWS Cloud HSM to encrypt the ML data volumes, and to encrypt the model artifacts and data in Amazon S3.

Answer: A

Explanation:
Explanation
Amazon SageMaker supports encryption at rest for the ML storage volumes, the model artifacts, and the data in Amazon S3 using AWS Key Management Service (AWS KMS). AWS KMS is a service that allows customers to create and manage encryption keys that can be used to encrypt data. AWS KMS also provides an audit trail of key usage by logging key events to AWS CloudTrail. Customers can use either AWS managed keys or customer managed keys to encrypt their data. AWS managed keys are created and managed by AWS on behalf of the customer, while customer managed keys are created and managed by the customer. Customer managed keys offer more control and flexibility over the key policies, permissions, and rotation. Therefore, to meet the requirements of the company, the best option is to use customer managed keys in AWS KMS to encrypt the ML data volumes, and to encrypt the model artifacts and data in Amazon S3.
The other options are not correct because:
Option A: AWS Cloud HSM is a service that provides hardware security modules (HSMs) to store and use encryption keys. AWS Cloud HSM is not integrated with Amazon SageMaker, and cannot be used to encrypt the ML data volumes, the model artifacts, or the data in Amazon S3. AWS Cloud HSM is more suitable for customers who need to meet strict compliance requirements or who need direct control over the HSMs.
Option B: SageMaker built-in transient keys are temporary keys that are used to encrypt the ML data volumes and are discarded immediately after encryption. These keys do not provide persistent encryption or logging of key usage. Enabling default encryption for new Amazon Elastic Block Store (Amazon EBS) volumes does not affect the ML data volumes, which are encrypted separately by SageMaker. Moreover, this option does not address the encryption of the model artifacts and data in Amazon S3.
Option D: AWS Security Token Service (AWS STS) is a service that provides temporary credentials to access AWS resources. AWS STS does not provide encryption keys or encryption services. AWS STS cannot be used to encrypt the ML storage volumes, the model artifacts, or the data in Amazon S3.
References:
Protect Data at Rest Using Encryption - Amazon SageMaker
What is AWS Key Management Service? - AWS Key Management Service
What is AWS CloudHSM? - AWS CloudHSM
What is AWS Security Token Service? - AWS Security Token Service


NEW QUESTION # 184
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 RDS and Amazon ES
  • B. Amazon S3 and Amazon Athena
  • C. Amazon DynamoDB and DynamoDB Accelerator (DAX)
  • D. Amazon Redshift and AWS Glue

Answer: D


NEW QUESTION # 185
......

If you have a faith, then go to defend it. Gorky once said that faith is a great emotion, a creative force. My dream is to become a top IT expert. I think that for me is nowhere in sight. But to succeed you can have a shortcut, as long as you make the right choice. I took advantage of SurePassExams's Amazon AWS-Certified-Machine-Learning-Specialty exam training materials, and passed the Amazon AWS-Certified-Machine-Learning-Specialty Exam. SurePassExams Amazon AWS-Certified-Machine-Learning-Specialty exam training materials is the best training materials. If you're also have an IT dream. Then go to buy SurePassExams's Amazon AWS-Certified-Machine-Learning-Specialty exam training materials, it will help you achieve your dreams.

Exam AWS-Certified-Machine-Learning-Specialty Study Solutions: https://www.surepassexams.com/AWS-Certified-Machine-Learning-Specialty-exam-bootcamp.html

What's more, part of that SurePassExams AWS-Certified-Machine-Learning-Specialty dumps now are free: https://drive.google.com/open?id=1q7Ya1ef2wKV3SUGc4-cHqcGP2UE4uExl

Report this page