Free Professional Machine Learning Engineer Exam Braindumps (page: 28)

Page 28 of 69

During batch training of a neural network, you notice that there is an oscillation in the loss. How should you adjust your model to ensure that it converges?

  1. Decrease the size of the training batch.
  2. Decrease the learning rate hyperparameter.
  3. Increase the learning rate hyperparameter.
  4. Increase the size of the training batch.

Answer(s): B



You work for a toy manufacturer that has been experiencing a large increase in demand. You need to build an ML model to reduce the amount of time spent by quality control inspectors checking for product defects. Faster defect detection is a priority. The factory does not have reliable Wi-Fi. Your company wants to implement the new ML model as soon as possible. Which model should you use?

  1. AutoML Vision Edge mobile-high-accuracy-1 model
  2. AutoML Vision Edge mobile-low-latency-1 model
  3. AutoML Vision model
  4. AutoML Vision Edge mobile-versatile-1 model

Answer(s): B



You need to build classification workflows over several structured datasets currently stored in BigQuery. Because you will be performing the classification several times, you want to complete the following steps without writing code: exploratory data analysis, feature selection, model building, training, and hyperparameter tuning and serving. What should you do?

  1. Train a TensorFlow model on Vertex AI.
  2. Train a classification Vertex AutoML model.
  3. Run a logistic regression job on BigQuery ML.
  4. Use scikit-learn in Notebooks with pandas library.

Answer(s): B



You are an ML engineer in the contact center of a large enterprise. You need to build a sentiment analysis tool that predicts customer sentiment from recorded phone conversations. You need to identify the best approach to building a model while ensuring that the gender, age, and cultural differences of the customers who called the contact center do not impact any stage of the model development pipeline and results. What should you do?

  1. Convert the speech to text and extract sentiments based on the sentences.
  2. Convert the speech to text and build a model based on the words.
  3. Extract sentiment directly from the voice recordings.
  4. Convert the speech to text and extract sentiment using syntactical analysis.

Answer(s): D



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Tina commented on April 09, 2024
Good questions
Anonymous
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Kavah commented on September 29, 2021
Very responsive and cool support team.
UNITED KINGDOM
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