Become Google Certified with updated Professional-Machine-Learning-Engineer exam questions and correct answers
You work for a large social network service provider whose users post articles and discuss news. Millions of comments are posted online each day, and more than 200 human moderators constantly review comments and flag those that are inappropriate. Your team is building an ML model to help human moderators check content on the platform. The model scores each comment and flags suspicious comments to be reviewed by a human. Which metric(s) should you use to monitor the model’s performance?
You built a deep learning-based image classification model by using on-premises data. You want to use Vertex
Al to deploy the model to production Due to security concerns you cannot move your data to the cloud. You
are aware that the input data distribution might change over time You need to detect model performance
changes in production. What should you do?
You work for a food product company. Your company’s historical sales data is stored in BigQuery.You need to use Vertex AI’s custom training service to train multiple TensorFlow models that read the data from BigQuery and predict future sales. You plan to implement a data preprocessing algorithm that performs mm-max scaling and bucketing on a large number of features before you start experimenting with the models. You want to minimize preprocessing time, cost, and development effort. How should you configure this workflow?
You are training an ML model on a large dataset. You are using a TPU to accelerate the training process You
notice that the training process is taking longer than expected. You discover that the TPU is not reaching its
full capacity. What should you do?
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