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Complete MLS-C01 Amazon Web Services Materials

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Total 322 questions

AWS Certified Machine Learning - Specialty Questions and Answers

Question 65

A financial services company wants to adopt Amazon SageMaker as its default data science environment. The company's data scientists run machine learning (ML) models on confidential financial data. The company is worried about data egress and wants an ML engineer to secure the environment.

Which mechanisms can the ML engineer use to control data egress from SageMaker? (Choose three.)

Options:

A.

Connect to SageMaker by using a VPC interface endpoint powered by AWS PrivateLink.

B.

Use SCPs to restrict access to SageMaker.

C.

Disable root access on the SageMaker notebook instances.

D.

Enable network isolation for training jobs and models.

E.

Restrict notebook presigned URLs to specific IPs used by the company.

F.

Protect data with encryption at rest and in transit. Use AWS Key Management Service (AWS KMS) to manage encryption keys.

Question 66

A Machine Learning Specialist has created a deep learning neural network model that performs well on the training data but performs poorly on the test data.

Which of the following methods should the Specialist consider using to correct this? (Select THREE.)

Options:

A.

Decrease regularization.

B.

Increase regularization.

C.

Increase dropout.

D.

Decrease dropout.

E.

Increase feature combinations.

F.

Decrease feature combinations.

Question 67

A web-based company wants to improve its conversion rate on its landing page Using a large historical dataset of customer visits, the company has repeatedly trained a multi-class deep learning network algorithm on Amazon SageMaker However there is an overfitting problem training data shows 90% accuracy in predictions, while test data shows 70% accuracy only

The company needs to boost the generalization of its model before deploying it into production to maximize conversions of visits to purchases

Which action is recommended to provide the HIGHEST accuracy model for the company's test and validation data?

Options:

A.

Increase the randomization of training data in the mini-batches used in training.

B.

Allocate a higher proportion of the overall data to the training dataset

C.

Apply L1 or L2 regularization and dropouts to the training.

D.

Reduce the number of layers and units (or neurons) from the deep learning network.

Question 68

A data scientist needs to create a model for predictive maintenance. The model will be based on historical data to identify rare anomalies in the data.

The historical data is stored in an Amazon S3 bucket. The data scientist needs to use Amazon SageMaker Data Wrangler to ingest the data. The data scientists also needs to perform exploratory data analysis (EDA) to understand the statistical properties of the data.

Which solution will meet these requirements with the LEAST amount of compute resources?

Options:

A.

Import the data by using the None option.

B.

Import the data by using the Stratified option.

C.

Import the data by using the First K option. Infer the value of K from domain knowledge.

D.

Import the data by using the Randomized option. Infer the random size from domain knowledge.

Page: 17 / 23
Total 322 questions