Google Professional Machine Learning Engineer
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As an ML engineer at a leading travel company, you've been tasked with optimizing the prediction models for customer vacation patterns. These models have shown that vacation destinations vary significantly by season and holidays, with patterns repeating annually. Your goal is to implement a solution that not only stores model versions and their performance statistics efficiently but also allows for easy comparison across different years to identify trends and improve model accuracy. Considering the need for scalability, cost-effectiveness, and the ability to handle large datasets, what is the BEST approach to achieve this? Choose the two most appropriate options.
As an ML engineer at a leading travel company, you've been tasked with optimizing the prediction models for customer vacation patterns. These models have shown that vacation destinations vary significantly by season and holidays, with patterns repeating annually. Your goal is to implement a solution that not only stores model versions and their performance statistics efficiently but also allows for easy comparison across different years to identify trends and improve model accuracy. Considering the need for scalability, cost-effectiveness, and the ability to handle large datasets, what is the BEST approach to achieve this? Choose the two most appropriate options.
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