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Successfully graduated students of HR Spot- Kolkata, wish you best of luck for your bright future... :)

“You Can’t Teach Employees To Smile. They Have To Smile Before You Hire Them.”

-Arte Nathan

I have learned from working on Machine Learning problems in the part, define and structure your problem up front! This is not a new principle to me - but in this matter it’s important to call it out and Highlight it.
In my experience, your matter of interest needs to be big enough to realistically have a chance of identifying statistical patterns in the data. There is no precise number here, but at least hundreds of observations of your matter of interest are needed. However, your matter also needs to be a relatively small proportion of your overall set to give you the best chance of separating them from random crash in your data – and people data has a lot of crash. The more your matter of interest goes over about 10% of your total sample, the less powerful your prediction is likely to be. The consequence of this is that your total hr data set should comprise at least a few thousand observations.

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Our successfully graduated students of Bhubaneswar. Wish You best of luck for your bright future... :)

Our successfully graduated students of Bhubaneswar. Wish You best of luck for your bright future... 😀

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