LATEST AI1-C01 DEMO & CERTIFICATION AI1-C01 BOOK TORRENT

Latest AI1-C01 Demo & Certification AI1-C01 Book Torrent

Latest AI1-C01 Demo & Certification AI1-C01 Book Torrent

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Amazon AWS Certified AI Practitioner Exam Sample Questions (Q19-Q24):

NEW QUESTION # 19
A company is developing a new model to predict the prices of specific items. The model performed well on the training dataset. When the company deployed the model to production, the model's performance decreased significantly.
What should the company do to mitigate this problem?

  • A. Add hyperparameters to the model.
  • B. Increase the model training time.
  • C. Increase the volume of data that is used in training.
  • D. Reduce the volume of data that is used in training.

Answer: C


NEW QUESTION # 20
A company has documents that are missing some words because of a database error. The company wants to build an ML model that can suggest potential words to fill in the missing text.
Which type of model meets this requirement?

  • A. Clustering models
  • B. BERT-based models
  • C. Topic modeling
  • D. Prescriptive ML models

Answer: B


NEW QUESTION # 21
A company is building an ML model. The company collected new data and analyzed the data by creating a correlation matrix, calculating statistics, and visualizing the data.
Which stage of the ML pipeline is the company currently in?

  • A. Hyperparameter tuning
  • B. Exploratory data analysis
  • C. Data pre-processing
  • D. Feature engineering

Answer: B


NEW QUESTION # 22
An AI practitioner is using an Amazon Bedrock base model to summarize session chats from the customer service department. The AI practitioner wants to store invocation logs to monitor model input and output data.
Which strategy should the AI practitioner use?

  • A. Configure model invocation logging in Amazon EventBridge.
  • B. Configure AWS Audit Manager as the logs destination for the model.
  • C. Enable invocation logging in Amazon Bedrock.
  • D. Configure AWS CloudTrail as the logs destination for the model.

Answer: C


NEW QUESTION # 23
A company uses Amazon SageMaker for its ML pipeline in a production environment. The company has large input data sizes up to 1 GB and processing times up to 1 hour. The company needs near real-time latency.
Which SageMaker inference option meets these requirements?

  • A. Asynchronous inference
  • B. Batch transform
  • C. Real-time inference
  • D. Serverless inference

Answer: C


NEW QUESTION # 24
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