Free Amazon MLS-C01 Exam Questions

Question 1

A machine learning specialist works for a fruit processing company and needs to build a system that

categorizes apples into three types. The specialist has collected a dataset that contains 150 images for each

type of apple and applied transfer learning on a neural network that was pretrained on ImageNet with this

dataset.

The company requires at least 85?curacy to make use of the model.

After an exhaustive grid search, the optimal hyperparameters produced the following:

68?curacy on the training set

67?curacy on the validation set

What can the machine learning specialist do to improve the system's accuracy?

A : Upload the model to an Amazon SageMaker notebook instance and use the Amazon SageMaker HPOfeature to optimize the model's hyperparameters.

B : more data to the training set and retrain the model using transfer learning to reduce the bias.

C : Use a neural network model with more layers that are pretrained on ImageNet and apply transfer learningto increase the variance.

D : ain a new model using the current neural network architecture.

Answer: B

Question 2

A data scientist is working on a public sector project for an urban traffic system. While studying the traffic patterns, it is clear to the data scientist that the traffic behavior at each light is correlated, subject to a small stochastic error term. The data scientist must model the traffic behavior to analyze the traffic patterns and reduce congestion.

How will the data scientist MOST effectively model the problem?

A : data scientist should obtain a correlated equilibrium policy by formulating this problem as a multi-agent reinforcement learning problem.

B : data scientist should obtain the optimal equilibrium policy by formulating this problem as a single-agent reinforcement learning problem.

C : ther than finding an equilibrium policy, the data scientist should obtain accurate predictors of traffic flow by using historical data through a supervised learning approach.

D : ther than finding an equilibrium policy, the data scientist should obtain accurate predictors of traffic flow by using unlabeled simulated data representing the new traffic patterns in the city and applying an unsupervised learning approach.

Answer: D

Question 3

Given the following confusion matrix for a movie classification model, what is the true class frequency for Romance and the predicted class frequency for Adventure?

A : true class frequency for Romance is 77.56% and the predicted class frequency for Adventure is 20 85%

B : true class frequency for Romance is 57.92% and the predicted class frequency for Adventure is 1312%

C : true class frequency for Romance is 0 78 and the predicted class frequency for Adventure is (0 47 - 0.32).

D : true class frequency for Romance is 77.56% * 0.78 and the predicted class frequency for Adventure is 20 85% ' 0.32

Answer: B

Question 4

A financial services company wants to automate its loan approval process by building a machine learning (ML) model. Each loan data point contains credit history from a third-party data source and demographic information about the customer. Each loan approval prediction must come with a report that contains an explanation for why the customer was approved for a loan or was denied for a loan. The company will use Amazon SageMaker to build the model. Which solution will meet these requirements with the LEAST development effort?

A : SageMaker Model Debugger to automatically debug the predictions, generate the explanation, and attach the explanation report.

B : AWS Lambda to provide feature importance and partial dependence plots. Use the plots to generate and attach the explanation report

C : SageMaker Clarify to generate the explanation report. Attach the report to the predicted results.

D : Use custom Amazon CloudWatch metrics to generate the explanation report. Attach the report to the predicted results.

Answer: A

Question 5

A company is training machine learning (ML) models on Amazon SageMaker by using 200 TB of data that is stored in Amazon S3 buckets. The training data consists of individual files that are each larger than 200 MB in size. The company needs a data access solution that offers the shortest processing time and the least amount of setup. Which solution will meet these requirements?

A : File mode in SageMaker to copy the dataset from the S3 buckets to the ML instance storage.

B : eate an Amazon FSx for Lustre file system. Link the file system to the S3 buckets.

C : eate an Amazon Elastic File System (Amazon EFS) file system. Mount the file system to the training instances

D : FastFile mode in SageMaker to stream the files on demand from the S3 buckets

Answer: D