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AN INTUITIVE SUMMARY OF MODEL SELECTION — PART 2: BIAS VARIANCE TRADE-OFF

We love all our children (algorithms) equally — but how can a deep neural network perform worse than a single-layer one? Part 2 of the Model Selection series: Bias, Variance, and why you can't just pick the biggest hypothesis space and call it a day.

DataScience4 years ago

AN INTUITIVE SUMMARY OF MODEL SELECTION — PART 1: NO FREE LUNCH THEOREMS

Why do we face "Wait! WHAT'S GOING ON!!" moments in ML? First post in my Model Selection series — starting with the No Free Lunch Theorem and why you should never fall in love with an algorithm.

DataScience4 years ago

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