An ML engineer has trained a neural network by using stochastic gradient descent (SGD). The neural network performs poorly on the test set. The values for training loss and validation loss remain high and show an oscillating pattern. The values decrease for a few epochs and then increase for a few epochs before repeating the same cycle.
What should the ML engineer do to improve the training process?

1. A. Introduce early stopping.
2. B. Increase the size of the test set.
3. C. Increase the learning rate.
4. D. Decrease the learning rate.

Correct Answer: D

A company has deployed an ML model that detects fraudulent credit card transactions in real time in a banking application. The model uses Amazon SageMaker Asynchronous Inference. Consumers are reporting delays in receiving the inference results.
An ML engineer needs to implement a solution to improve the inference performance. The solution also must provide a notification when a deviation in model quality occurs.
Which solution will meet these requirements?

1. A. Use SageMaker real-time inference for inferenc
2. B. Use SageMaker Model Monitor for notifications about model quality.
3. C. Use SageMaker batch transform for inferenc
4. D. Use SageMaker Model Monitor for notifications about model quality.
5. E. Use SageMaker Serverless Inference for inferenc
6. F. Use SageMaker Inference Recommender for notifications about model quality.
7. G. Keep using SageMaker Asynchronous Inference for inferenc
8. H. Use SageMaker Inference Recommender for notifications about model quality.

Correct Answer: A

A company has used Amazon SageMaker to deploy a predictive ML model in production. The company is using SageMaker Model Monitor on the model. After a model update, an ML engineer notices data quality issues in the Model Monitor checks.
What should the ML engineer do to mitigate the data quality issues that Model Monitor has identified?

1. A. Adjust the model's parameters and hyperparameters.
2. B. Initiate a manual Model Monitor job that uses the most recent production data.
3. C. Create a new baseline from the latest datase
4. D. Update Model Monitor to use the new baseline for evaluations.
5. E. Include additional data in the existing training set for the mode
6. F. Retrain and redeploy the model.

Correct Answer: C

A company has a conversational AI assistant that sends requests through Amazon Bedrock to an Anthropic Claude large language model (LLM). Users report that when they ask similar questions multiple times, they sometimes receive different answers. An ML engineer needs to improve the responses to be more consistent and less random.
Which solution will meet these requirements?

1. A. Increase the temperature parameter and the top_k parameter.
2. B. Increase the temperature paramete
3. C. Decrease the top_k parameter.
4. D. Decrease the temperature paramete
5. E. Increase the top_k parameter.
6. F. Decrease the temperature parameter and the top_k parameter.

Correct Answer: D

A company needs to give its ML engineers appropriate access to training data. The ML engineers must access training data from only their own business group. The ML engineers must not be allowed to access training data from other business groups.
The company uses a single AWS account and stores all the training data in Amazon S3 buckets. All ML model training occurs in Amazon SageMaker.
Which solution will provide the ML engineers with the appropriate access?

1. A. Enable S3 bucket versioning.
2. B. Configure S3 Object Lock settings for each user.
3. C. Add cross-origin resource sharing (CORS) policies to the S3 buckets.
4. D. Create IAM policie
5. E. Attach the policies to IAM users or IAM roles.

Correct Answer: D