AWS-Certified-Machine-Learning-Specialty Exam Question 46

A Machine Learning Specialist is training a model to identify the make and model of vehicles in images. The Specialist wants to use transfer learning and an existing model trained on images of general objects. The Specialist collated a large custom dataset of pictures containing different vehicle makes and models.
What should the Specialist do to initialize the model to re-train it with the custom data?
  • AWS-Certified-Machine-Learning-Specialty Exam Question 47

    A Machine Learning Specialist is designing a system for improving sales for a company. The objective is to use the large amount of information the company has on users' behavior and product preferences to predict which products users would like based on the users' similarity to other users.
    What should the Specialist do to meet this objective?
  • AWS-Certified-Machine-Learning-Specialty Exam Question 48

    While reviewing the histogram for residuals on regression evaluation data a Machine Learning Specialist notices that the residuals do not form a zero-centered bell shape as shown What does this mean?
  • AWS-Certified-Machine-Learning-Specialty Exam Question 49

    A machine learning (ML) specialist is using Amazon SageMaker hyperparameter optimization (HPO) to improve a model's accuracy. The learning rate parameter is specified in the following HPO configuration:

    During the results analysis, the ML specialist determines that most of the training jobs had a learning rate between 0.01 and 0.1. The best result had a learning rate of less than 0.01. Training jobs need to run regularly over a changing dataset. The ML specialist needs to find a tuning mechanism that uses different learning rates more evenly from the provided range between MinValue and MaxValue.
    Which solution provides the MOST accurate result?
  • AWS-Certified-Machine-Learning-Specialty Exam Question 50

    A Machine Learning team uses Amazon SageMaker to train an Apache MXNet handwritten digit classifier model using a research dataset. The team wants to receive a notification when the model is overfitting.
    Auditors want to view the Amazon SageMaker log activity report to ensure there are no unauthorized API calls.
    What should the Machine Learning team do to address the requirements with the least amount of code and fewest steps?