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There's an app with over 50 services. I have the data on the type of service a specific customer (they have a unique customer number) does on the app, the date, location, time, duration on a service and the volume of that service. I want to build a ML model to personalize the services the customer gets daily when they open the app. i.e. Top 6 services they're likely to use for that day Which machine learning technique would be optimal to achieving this?

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Start with the most frequent used ones... then explore the need to build a more complex model. Chances are the distribution of service is skewed and you don’t really need to build a model outside a top n.

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