MLS-C01AWS Certified Machine Learning - Specialty (MLS-C01)
340 Questions and Answers Experienced specialists selected 340 questions for this exam. All answers are verified to ensure correctness.
Last Updated Apr 30, 2024 Ace your exams with our consistently updated MLS-C01 exam dumps.
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MLS-C01 Online Practice Questions and Answers
A machine learning (ML) specialist is training a multilayer perceptron (MLP) on a dataset with multiple classes. The target class of interest is unique compared to the other classes in the dataset, but it does not achieve an acceptable recall metric. The ML specialist varies the number and size of the MLP's hidden layers, but the results do not improve significantly.
Which solution will improve recall in the LEAST amount of time?
A. Add class weights to the MLP's loss function, and then retrain.
B. Gather more data by using Amazon Mechanical Turk, and then retrain.
C. Train a k-means algorithm instead of an MLP.
D. Train an anomaly detection model instead of an MLP.
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?
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.
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?
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.
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Amazon MLS-C01 exam official information: This credential helps organizations identify and develop talent with critical skills for implementing cloud initiatives. Earning AWS Certified Machine Learning - Specialty validates expertise in building, training, tuning, and deploying machine learning (ML) models on AWS.
