Amazon (MLS-C01) Exam Questions And Answers page 11
A Machine Learning Specialist is assigned a TensorFlow project using Amazon SageMaker for training, and needs to continue working for an extended period with no Wi-Fi access.
Which approach should the Specialist use to continue working?
Which approach should the Specialist use to continue working?
Download the TensorFlow Docker container used in Amazon SageMaker from GitHub to their local environment, and use the Amazon SageMaker Python SDK to test the code.
Download TensorFlow from tensorflow.org to emulate the TensorFlow kernel in the SageMaker environment.
Download the SageMaker notebook to their local environment, then install Jupyter Notebooks on their laptop and continue the development in a local notebook.
Model Development
Machine Learning Implementation and Operations
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?
Which parameter tuning guidelines should the Specialist follow to avoid overfitting?
Increase the max_depth parameter value.
Lower the max_depth parameter value.
Update the objective to binary:logistic.
Lower the min_child_weight parameter value.
Model Development
Machine Learning Implementation and Operations
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?
Which parameter tuning guidelines should the Specialist follow to avoid overfitting?
Increase the max_depth parameter value.
Lower the max_depth parameter value.
Update the objective to binary:logistic.
Lower the min_child_weight parameter value.
Model Development
Machine Learning Implementation and Operations
A Machine Learning Specialist is attempting to build a linear regression model.
Given the displayed residual plot only, what is the MOST likely problem with the model?
Given the displayed residual plot only, what is the MOST likely problem with the model?
Linear regression is inappropriate. The residuals do not have constant variance.
Linear regression is inappropriate. The underlying data has outliers.
Linear regression is appropriate. The residuals have a zero mean.
Linear regression is appropriate. The residuals have constant variance.
Model Development
Machine Learning Implementation and Operations
A Machine Learning Specialist is attempting to build a linear regression model.
Given the displayed residual plot only, what is the MOST likely problem with the model?
Given the displayed residual plot only, what is the MOST likely problem with the model?
Linear regression is inappropriate. The residuals do not have constant variance.
Linear regression is inappropriate. The underlying data has outliers.
Linear regression is appropriate. The residuals have a zero mean.
Linear regression is appropriate. The residuals have constant variance.
Model Development
Machine Learning Implementation and Operations
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?
Which function will produce the desired output?
Dropout
Smooth L1 loss
Softmax
Rectified linear units (ReLU)
Model Development
Machine Learning Implementation and Operations
A Machine Learning Specialist is building a logistic regression model that will predict whether or not a person will order a pizza. The Specialist is trying to build the optimal model with an ideal classification threshold.
What model evaluation technique should the Specialist use to understand how different classification thresholds will impact the model's performance?
What model evaluation technique should the Specialist use to understand how different classification thresholds will impact the model's performance?
Receiver operating characteristic (ROC) curve
Misclassification rate
Root Mean Square Error (RMSE)
L1 norm
Model Development
Machine Learning Implementation and Operations
A Machine Learning Specialist is building a model that will perform time series forecasting using Amazon SageMaker. The Specialist has finished training the model and is now planning to perform load testing on the endpoint so they can configure Auto Scaling for the model variant.
Which approach will allow the Specialist to review the latency, memory utilization, and CPU utilization during the load test?
Which approach will allow the Specialist to review the latency, memory utilization, and CPU utilization during the load test?
Review SageMaker logs that have been written to Amazon S3 by leveraging Amazon Athena and Amazon QuickSight to visualize logs as they are being produced.
Generate an Amazon CloudWatch dashboard to create a single view for the latency, memory utilization, and CPU utilization metrics that are outputted by Amazon SageMaker.
Build custom Amazon CloudWatch Logs and then leverage Amazon ES and Kibana to query and visualize the log data as it is generated by Amazon SageMaker.
Send Amazon CloudWatch Logs that were generated by Amazon SageMaker to Amazon ES and use Kibana to query and visualize the log data.
Machine Learning Implementation and Operations
AWS Machine Learning Services
A Machine Learning Specialist is building a prediction model for a large number of features using linear models, such as linear regression and logistic regression. During exploratory data analysis, the Specialist observes that many features are highly correlated with each other. This may make the model unstable.
What should be done to reduce the impact of having such a large number of features?
What should be done to reduce the impact of having such a large number of features?
Perform one-hot encoding on highly correlated features.
Use matrix multiplication on highly correlated features.
Create a new feature space using principal component analysis (PCA)
Apply the Pearson correlation coefficient.
Exploratory Data Analysis
Model Development
A Machine Learning Specialist is configuring Amazon SageMaker so multiple Data Scientists can access notebooks, train models, and deploy endpoints. To ensure the best operational performance, the Specialist needs to be able to track how often the Scientists are deploying models, GPU and CPU utilization on the deployed SageMaker endpoints, and all errors that are generated when an endpoint is invoked.
Which services are integrated with Amazon SageMaker to track this information? (Choose two.)
Which services are integrated with Amazon SageMaker to track this information? (Choose two.)
AWS Health
AWS Trusted Advisor
Amazon CloudWatch
AWS Config
AWS CloudTrail
Model Development
Machine Learning Implementation and Operations
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