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Order the reasoning steps for deciding how to handle the absence of user data when constructing dev/test sets before a mobile app launches.
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Before a mobile app launches, how can you approximate future dev/test data when no user data is available?
Before a mobile app launches, it is impossible to approximate the future data distribution for dev/test sets.
Before launching a mobile app, you can approximate future user data by asking friends to take _____ pictures of cats and send them to you.
When a mobile app has not yet launched and no user data is available, what is the recommended approach for building dev/test sets?
Before a mobile app launches, it is impossible to construct any dev/test set because real user data does not yet exist.
When no user data exists before app launch, Andrew Ng recommends trying to _____ the future data distribution for dev/test sets.
Match each pre-launch data concept to its correct description.
Order the steps a team should follow to approximate pre-launch dev/test data for a mobile app.
Which specific example does Andrew Ng give in Machine Learning Yearning for approximating pre-launch mobile app data for a cat-detection use case?
Data collected from friends before a mobile app's launch perfectly represents the distribution of future user data.
Andrew Ng suggests asking your _____ to take mobile-phone pictures of cats as one way to approximate pre-launch user data.
Match each pre-launch data approximation term to its correct explanation.
Order the reasoning steps for deciding how to handle the absence of user data when constructing dev/test sets before a mobile app launches.
Explain the rationale and challenges of approximating future dev/test data before a mobile application launch.
Case Study: Designing a cat detection dev/test set before mobile application launch.
What is the purpose of asking friends to take photos when constructing a pre-launch dev/test set?