Free Professional Machine Learning Engineer Exam Braindumps (page: 39)

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You work for a bank and are building a random forest model for fraud detection. You have a dataset that includes transactions, of which 1% are identified as fraudulent. Which data transformation strategy would likely improve the performance of your classifier?

  1. Modify the target variable using the Box-Cox transformation.
  2. Z-normalize all the numeric features.
  3. Oversample the fraudulent transaction 10 times.
  4. Log transform all numeric features.

Answer(s): C



You are developing a classification model to support predictions for your company’s various products. The dataset you were given for model development has class imbalance You need to minimize false positives and false negatives What evaluation metric should you use to properly train the model?

  1. F1 score
  2. Recall
  3. Accuracy
  4. Precision

Answer(s): A



You are training an object detection machine learning model on a dataset that consists of three million X-ray images, each roughly 2 GB in size. You are using Vertex AI Training to run a custom training application on a Compute Engine instance with 32-cores, 128 GB of RAM, and 1 NVIDIA P100 GPU. You notice that model training is taking a very long time. You want to decrease training time without sacrificing model performance. What should you do?

  1. Increase the instance memory to 512 GB, and increase the batch size.
  2. Replace the NVIDIA P100 GPU with a K80 GPU in the training job.
  3. Enable early stopping in your Vertex AI Training job.
  4. Use the tf.distribute.Strategy API and run a distributed training job.

Answer(s): D



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 Vertex AI Workbench user-managed notebooks with pandas library.

Answer(s): B



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