AWS Certified Machine Learning Engineer – Associate226 questions across 23 pages are complete and free, with no account or card.
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A company needs to deploy a custom-trained classification ML model on AWS. The model must make near real-time predictions with low latency and must handle variable request volumes. Which solution will meet these requirements?
Answer: C
A company runs a neural network model and retrains the model when the performance degrades. The company uses a training job that uses Amazon SageMaker AI distributed data parallelism (DDP). The training job takes several hours to run. The company wants to decrease the required time for the training job. Which solution will meet this requirement?
Answer: D
An ML engineer decides to use Amazon SageMaker AI automated model tuning (AMT) for hyperparameter optimization (HPO). The ML engineer requires a tuning strategy that uses regression to slowly and sequentially select the next set of hyperparameters based on previous runs. The strategy must work across small hyperparameter ranges. Which solution will meet these requirements?
Answer: C
A healthcare company wants to detect irregularities in patient vital signs that could indicate early signs of a medical condition. The company has an unlabeled dataset that includes patient health records, medication history, and lifestyle changes. Which algorithm and hyperparameter should the company use to meet this requirement?
Answer: D
An ML engineer at an entertainment company is refining an ML model to predict audience preferences. As the model learns from data, the ML engineer notices that the model’s performance peaks early and then begins to gradually decline. The ML engineer must prevent the performance degradation after initial success. Which solution will meet this requirement?
Answer: B
An ML engineer is tuning an image classification model that shows poor performance on one of two available classes during prediction. Analysis reveals that the images whose class the model performed poorly on represent an extremely small fraction of the whole training dataset. The ML engineer must improve the model’s performance. Which solution will meet this requirement?
Answer: B
An ML engineer needs to develop an AI assistant by using Retrieval Augmented Generation (RAG) in Amazon Bedrock. The company stores a collection of PDF text files in an Amazon S3 bucket. The ML engineer must create an Amazon Bedrock knowledge base to process the PDF files and to store the processed files in a vector store. Which solution will meet these requirements?
Answer: D
An ML engineer needs to build a processing pipeline to identify and remove personally identifiable information (PII) from petabytes of unstructured data. The ML engineer will use the processed data to train ML models in Amazon SageMaker AI. Which solution will meet these requirements?
Answer: A
A company develops a recommendation model and hosts the model on an Amazon SageMaker AI endpoint. The model uses the SageMaker AI endpoint to perform near real-time inference to deliver personalized product recommendations to customers based on browsing history, purchase records, and in-app user interactions. After a major marketing campaign, the company observes a sharp drop in the model’s performance. The company needs a solution to proactively monitor, detect, and validate model performance before future marketing campaigns. Which solution will meet these requirements?
Answer: D
A company is using Amazon SageMaker AI to create a classification model to categorize the company’s sales performance for each month of the previous 20 years on a scale from 1 to 5. The dataset includes fields for month, sales region, regional aggregate sales, and the number of stores in each sales region. The company notices that during two months of every year, the aggregate sales values are unexpectedly high. The company performs one-hot encoding on all non-numerical features in the training and validation datasets. The company uses the training dataset to train the classification model. When the company evaluates the model against the validation dataset, the results are less accurate than expected. The company must improve the model’s accuracy on the validation dataset. Which solution will meet this requirement?
Answer: B
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MLA-C01 practice, question 201. 226 questions available.
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