datascience.interview

Most candidates get rejected because they confuse this 👇
✅ Feature Engineering = create / transform better signals
✂️ Feature Selection = remove noise / keep the best features

Comment E or S and I’ll post the next reel with methods + examples 🔥
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A strong ML project is not enough to clear interviews.

This is why good candidates still get rejected.

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