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Amazon Web Services MLS-C01 Exam Dumps Questions and Answers

Exam Code: MLS-C01
Certification: AWS Certified Specialty
Last Update: Nov 27, 2022
Questions: 208
10  Customers Passed Amazon Web Services MLS-C01
90%  Average Success In Real Exam
88%  Questions came word by word from this dump
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AWS Certified Machine Learning - Specialty Questions and Answers

Questions 1

A Machine Learning Specialist is assigned to a Fraud Detection team and must tune an XGBoost model, which

is working appropriately for test data. However, with unknown data, it is not working as expected. The existing

parameters are provided as follows.

Which parameter tuning guidelines should the Specialist follow to avoid overfitting?

Options:

A.

Increase the max_depth parameter value.

B.

Lower the max_depth parameter value.

C.

Update the objective to binary:logistic.

D.

Lower the min_child_weight parameter value.

Questions 2

A retail company uses a machine learning (ML) model for daily sales forecasting. The company’s brand manager reports that the model has provided inaccurate results for the past 3 weeks.

At the end of each day, an AWS Glue job consolidates the input data that is used for the forecasting with the actual daily sales data and the predictions of the model. The AWS Glue job stores the data in Amazon S3. The company’s ML team is using an Amazon SageMaker Studio notebook to gain an understanding about the source of the model's inaccuracies.

What should the ML team do on the SageMaker Studio notebook to visualize the model's degradation MOST accurately?

Options:

A.

Create a histogram of the daily sales over the last 3 weeks. In addition, create a histogram of the daily sales from before that period.

B.

Create a histogram of the model errors over the last 3 weeks. In addition, create a histogram of the model errors from before that period.

C.

Create a line chart with the weekly mean absolute error (MAE) of the model.

D.

Create a scatter plot of daily sales versus model error for the last 3 weeks. In addition, create a scatter plot of daily sales versus model error from before that period.

Questions 3

A data scientist has a dataset of machine part images stored in Amazon Elastic File System (Amazon EFS). The data scientist needs to use Amazon SageMaker to create and train an image classification machine learning model based on this dataset. Because of budget and time constraints, management wants the data scientist to create and train a model with the least number of steps and integration work required.

How should the data scientist meet these requirements?

Options:

A.

Mount the EFS file system to a SageMaker notebook and run a script that copies the data to an Amazon FSx for Lustre file system. Run the SageMaker training job with the FSx for Lustre file system as the data source.

B.

Launch a transient Amazon EMR cluster. Configure steps to mount the EFS file system and copy the data to an Amazon S3 bucket by using S3DistCp. Run the SageMaker training job with Amazon S3 as the data source.

C.

Mount the EFS file system to an Amazon EC2 instance and use the AWS CLI to copy the data to an Amazon S3 bucket. Run the SageMaker training job with Amazon S3 as the data source.

D.

Run a SageMaker training job with an EFS file system as the data source.