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

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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: 281 Q&A's Shared By: nayla
Question 60

A Machine Learning Specialist is building a convolutional neural network (CNN) that will classify 10 types of animals. The Specialist has built a series of layers in a neural network that will take an input image of an animal, pass it through a series of convolutional and pooling layers, and then finally pass it through a dense and fully connected layer with 10 nodes The Specialist would like to get an output from the neural network that is a probability distribution of how likely it is that the input image belongs to each of the 10 classes

Which function will produce the desired output?

Options:

A.

Dropout

B.

Smooth L1 loss

C.

Softmax

D.

Rectified linear units (ReLU)

Discussion
Question 61

A company deployed a machine learning (ML) model on the company website to predict real estate prices. Several months after deployment, an ML engineer notices that the accuracy of the model has gradually decreased.

The ML engineer needs to improve the accuracy of the model. The engineer also needs to receive notifications for any future performance issues.

Which solution will meet these requirements?

Options:

A.

Perform incremental training to update the model. Activate Amazon SageMaker Model Monitor to detect model performance issues and to send notifications.

B.

Use Amazon SageMaker Model Governance. Configure Model Governance to automatically adjust model hyper para meters. Create a performance threshold alarm in Amazon CloudWatch to send notifications.

C.

Use Amazon SageMaker Debugger with appropriate thresholds. Configure Debugger to send Amazon CloudWatch alarms to alert the team Retrain the model by using only data from the previous several months.

D.

Use only data from the previous several months to perform incremental training to update the model. Use Amazon SageMaker Model Monitor to detect model performance issues and to send notifications.

Discussion
Question 62

A city wants to monitor its air quality to address the consequences of air pollution A Machine Learning Specialist needs to forecast the air quality in parts per million of contaminates for the next 2 days in the city as this is a prototype, only daily data from the last year is available

Which model is MOST likely to provide the best results in Amazon SageMaker?

Options:

A.

Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the single time series consisting of

the full year of data with a predictor_type of regressor.

B.

Use Amazon SageMaker Random Cut Forest (RCF) on the single time series consisting of the full year of

data.

C.

Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year

of data with a predictor_type of regressor.

D.

Use the Amazon SageMaker Linear Learner algorithm on the single time series consisting of the full year

of data with a predictor_type of classifier.

Discussion
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Question 63

A Machine Learning Specialist works for a credit card processing company and needs to predict which transactions may be fraudulent in near-real time. Specifically, the Specialist must train a model that returns the probability that a given transaction may be fraudulent

How should the Specialist frame this business problem'?

Options:

A.

Streaming classification

B.

Binary classification

C.

Multi-category classification

D.

Regression classification

Discussion
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