it contains the miscellaneous attributes such as flags , which does belong to the main dimension table.
for eg; In a sales order fact table ,some informations like,
web-order , whether this is a online order or not
new_cust , Is this person a new customer ?
verification , whether the order has been verified?
Tell me how is kNN different from kmeans clustering?
Tell me why is resampling done?
Explain me do gradient descent methods at all times converge to a similar point?
Tell us how do clean up and organize big data sets?
Tell us how do you identify a barrier to performance?
Tell us why do we have max-pooling in classification CNNs?
Tell me how do you handle missing or corrupted data in a dataset?
What is dimensionality reduction, where it’s used, and it’s benefits?
Do you know what is the goal of A/B Testing?
Explain me what tools or devices help you succeed in your role as a data scientist?
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