Amazon MLA-C01 Online Practice Questions and Exam Preparation

Amazon MLA-C01 Online Questions & Answers

• Question 121:

  Which metric is most appropriate for evaluating a binary classification model with imbalanced classes?

  A. Accuracy
  B. Precision-Recall AUC
  C. Mean Squared Error (MSE)
  D. R-squared
  B. Precision-Recall AUC

• Question 122:

  An ML engineer is developing a fraud detection model on AWS. The training dataset includes transaction logs, customer profiles, and tables from an on-premises MySQL database. The transaction logs and customer profiles are stored in Amazon S3. The dataset has a class imbalance that affects the learning of the model's algorithm. Additionally, many of the features have interdependencies. The algorithm is not capturing all the desired underlying patterns in the data. Which AWS service or feature can aggregate the data from the various data sources?

  A. Amazon EMR Spark jobs
  B. Amazon Kinesis Data Streams
  C. Amazon DynamoDB
  D. AWS Lake Formation
  A. Amazon EMR Spark jobs

• Question 123:

  An ML engineer needs to use an ML model to predict the price of apartments in a specific location. Which metric should the ML engineer use to evaluate the model's performance?

  A. Accuracy
  B. Area Under the ROC Curve (AUC)
  C. F1 score
  D. Mean absolute error (MAE)
  D. Mean absolute error (MAE)

• Question 124:

  HOTSPOT

  An ML engineer is building a generative AI application on Amazon Bedrock by using large language models (LLMs). Select the correct generative AI term from the following list for each description. Each term should be selected one time or not at all. (Select three.)

  1. Embedding

  2. Retrieval Augmented Generation (RAG)

  3. Temperature

  4. Token