MLS-C01 Specialist Practice Questions

A Machine Learning Specialist built an image classification deep learning model. However the Specialist ran into an overfitting problem in which the training and testing accuracies were 99% and 75%r respectively. How should the Specialist address this issue and what is the reason behind it?

• AA. The learning rate should be increased because the optimization process was trapped at a local minimum.
• BB. The dropout rate at the flatten layer should be increased because the model is not generalized enough.
• CC. The dimensionality of dense layer next to the flatten layer should be increased because the model is not complex enough.
• DD. The epoch number should be increased because the optimization process was terminated before it reached the global minimum.

A Machine Learning Specialist wants to determine the appropriate SageMakerVariant Invocations Per Instance setting for an endpoint automatic scaling configuration. The Specialist has performed a load test on a single instance and determined that peak requests per second (RPS) without service degradation is about 20 RPS As this is the first deployment, the Specialist intends to set the invocation safety factor to 0 5 Based on the stated parameters and given that the invocations per instance setting is measured on a per-minute basis, what should the Specialist set as the sageMakervariantinvocationsPerinstance setting?

• AA. 10
• BB. 30
• CC. 600
• DD. 2,400

A Machine Learning Specialist was given a dataset consisting of unlabeled data The Specialist must create a model that can help the team classify the data into different buckets What model should be used to complete this work?

• AA. K-means clustering
• BB. Random Cut Forest (RCF)
• CC. XGBoost
• DD. BlazingText

A Machine Learning Specialist is working for a credit card processing company and receives an unbalanced dataset containing credit card transactions. It contains 99,000 valid transactions and 1,000 fraudulent transactions The Specialist is asked to score a model that was run against the dataset The Specialist has been advised that identifying valid transactions is equally as important as identifying fraudulent transactions What metric is BEST suited to score the model?

• AA. Precision
• BB. Recall
• CC. Area Under the ROC Curve (AUC)
• DD. Root Mean Square Error (RMSE)

While working on a neural network project, a Machine Learning Specialist discovers thai some features in the data have very high magnitude resulting in this data being weighted more in the cost function What should the Specialist do to ensure better convergence during backpropagation?

• AA. Dimensionality reduction
• BB. Data normalization
• CC. Model regulanzation
• DD. Data augmentation for the minority class

A Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training The Specialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs What does the Specialist need to do1?

• AA. Bundle the NVIDIA drivers with the Docker image
• BB. Build the Docker container to be NVIDIA-Docker compatible
• CC. Organize the Docker container's file structure to execute on GPU instances.
• DD. Set the GPU flag in the Amazon SageMaker Create TrainingJob request body