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

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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: 330 Q&A's Shared By: theia
Question 68

An insurance company is creating an application to automate car insurance claims. A machine learning (ML) specialist used an Amazon SageMaker Object Detection - TensorFlow built-in algorithm to train a model to detect scratches and dents in images of cars. After the model was trained, the ML specialist noticed that the model performed better on the training dataset than on the testing dataset.

Which approach should the ML specialist use to improve the performance of the model on the testing data?

Options:

A.

Increase the value of the momentum hyperparameter.

B.

Reduce the value of the dropout_rate hyperparameter.

C.

Reduce the value of the learning_rate hyperparameter.

D.

Increase the value of the L2 hyperparameter.

Discussion
Question 69

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?

Options:

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

Discussion
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Question 70

A Machine Learning Specialist is working with multiple data sources containing billions of records that need to be joined. What feature engineering and model development approach should the Specialist take with a dataset this large?

Options:

A.

Use an Amazon SageMaker notebook for both feature engineering and model development

B.

Use an Amazon SageMaker notebook for feature engineering and Amazon ML for model development

C.

Use Amazon EMR for feature engineering and Amazon SageMaker SDK for model development

D.

Use Amazon ML for both feature engineering and model development.

Discussion
Question 71

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?

Options:

A.

Logistic regression

B.

Random Cut Forest (RCF)

C.

Principal component analysis (PCA)

D.

Linear regression

Discussion
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