Google Professional Machine Learning Engineer
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As a professional working for a public transportation company, you are tasked with developing a model to predict delay times across various routes. These predictions will be delivered to users in real-time via an app. Given that seasonal changes and population growth affect data relevance, the model requires monthly retraining. The solution must adhere to Google's recommended best practices, be cost-effective, scalable, and ensure minimal downtime during retraining. Considering these constraints, how would you design the end-to-end architecture for this predictive model? Choose the two best options.
As a professional working for a public transportation company, you are tasked with developing a model to predict delay times across various routes. These predictions will be delivered to users in real-time via an app. Given that seasonal changes and population growth affect data relevance, the model requires monthly retraining. The solution must adhere to Google's recommended best practices, be cost-effective, scalable, and ensure minimal downtime during retraining. Considering these constraints, how would you design the end-to-end architecture for this predictive model? Choose the two best options.
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