Become Google Certified with updated Professional-Machine-Learning-Engineer exam questions and correct answers
You work at a large organization that recently decided to move their ML and data workloads to Google Cloud. The data engineering team has exported the structured data to a Cloud Storage bucket in Avro format. You need to propose a workflow that performs analytics, creates features, and hosts the features that your ML models use for online prediction. How should you configure the pipeline?
You work for a company that is developing an application to help users with meal planning You want to use
machine learning to scan a corpus of recipes and extract each ingredient (e g carrot, rice pasta) and each
kitchen cookware (e.g. bowl, pot spoon) mentioned Each recipe is saved in an unstructured text file What
should you do?
You have been given a dataset with sales predictions based on your company’s marketing activities. The data is structured and stored in BigQuery, and has been carefully managed by a team of data analysts. You need to prepare a report providing insights into the predictive capabilities of the data. You were asked to run several ML models with different levels of sophistication, including simple models and multilayered neural networks. You only have a few hours to gather the results of your experiments. Which Google Cloud tools should you use to complete this task in the most efficient and self-serviced way?
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