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NEW QUESTION 54
You have been asked to develop an input pipeline for an ML training model that processes images from disparate sources at a low latency. You discover that your input data does not fit in memory. How should you create a dataset following Google-recommended best practices?
Answer: C
NEW QUESTION 55
You work for a global footwear retailer and need to predict when an item will be out of stock based on historical inventory dat a. Customer behavior is highly dynamic since footwear demand is influenced by many different factors. You want to serve models that are trained on all available data, but track your performance on specific subsets of data before pushing to production. What is the most streamlined and reliable way to perform this validation?
Answer: D
Explanation:
https://www.tensorflow.org/tfx/guide/evaluator
NEW QUESTION 56
Which of the following metrics should a Machine Learning Specialist generally use to compare/evaluate machine learning classification models against each other?
Answer: A
NEW QUESTION 57
You need to train a regression model based on a dataset containing 50,000 records that is stored in BigQuery. The data includes a total of 20 categorical and numerical features with a target variable that can include negative values. You need to minimize effort and training time while maximizing model performance. What approach should you take to train this regression model?
Answer: D
Explanation:
https://cloud.google.com/bigquery-ml/docs/introduction
NEW QUESTION 58
You work on a growing team of more than 50 data scientists who all use AI Platform. You are designing a strategy to organize your jobs, models, and versions in a clean and scalable way. Which strategy should you choose?
Answer: C
NEW QUESTION 59
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