Why we need experimental frameworks for creating new models?
The answer is that when you are planning to create a personalized model, which
is nothing but a blend of your small experiments, carefully chosen algorithms,
and a cup of common sense, then you need a fail-safe, sophisticated, and user-friendly
ground where you can test your creative model, right? Particularly, if you are
an experimenter with non-IT background, you need something very cool,
easy-to-use, and simple experimental framework; using which you can test your
innovative analytical models.
Actually, it is here where you check your understanding of
your customers at a high scale. The overall idea is that your experimental
framework should be in a position to understand your hypothesis and do the
needed rest; it should allow you to enforce your experimental techniques at a
scale and speed that you are OK with. Having data and sophisticated algorithms
alone cannot ensure that you can create a better experience to your users. You
need to anchor your actions in meaningful and result-oriented experiments to
create an innovative and successful model using a solid experimental framework.
In summary,
experimental framework acts as your testing ground where you can check your creative
innovative models in a fail-safe mode before you start testing them on your real-time
data.
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