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Amazon Web Services MLS-C01 Dumps Questions Answers

MLS-C01 exam

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AWS Certified Machine Learning - Specialty

Last Update Mar 19, 2023
Total Questions : 208

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Last Update Mar 19, 2023
Total Questions : 208

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Total Questions : 208

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AWS Certified Machine Learning - Specialty Questions and Answers

Questions 1

A Data Scientist is building a model to predict customer churn using a dataset of 100 continuous numerical

features. The Marketing team has not provided any insight about which features are relevant for churn

prediction. The Marketing team wants to interpret the model and see the direct impact of relevant features on

the model outcome. While training a logistic regression model, the Data Scientist observes that there is a wide

gap between the training and validation set accuracy.

Which methods can the Data Scientist use to improve the model performance and satisfy the Marketing team’s

needs? (Choose two.)



Add L1 regularization to the classifier


Add features to the dataset


Perform recursive feature elimination


Perform t-distributed stochastic neighbor embedding (t-SNE)


Perform linear discriminant analysis

Questions 2

A Machine Learning Specialist needs to move and transform data in preparation for training Some of the data needs to be processed in near-real time and other data can be moved hourly There are existing Amazon EMR MapReduce jobs to clean and feature engineering to perform on the data

Which of the following services can feed data to the MapReduce jobs? (Select TWO )





Amazon Kinesis


AWS Data Pipeline


Amazon Athena


Amazon ES

Questions 3

An insurance company is developing a new device for vehicles that uses a camera to observe drivers' behavior and alert them when they appear distracted The company created approximately 10,000 training images in a controlled environment that a Machine Learning Specialist will use to train and evaluate machine learning models

During the model evaluation the Specialist notices that the training error rate diminishes faster as the number of epochs increases and the model is not accurately inferring on the unseen test images

Which of the following should be used to resolve this issue? (Select TWO)



Add vanishing gradient to the model


Perform data augmentation on the training data


Make the neural network architecture complex.


Use gradient checking in the model


Add L2 regularization to the model