A Few Useful Things to Know about Machine Learning.md

#artificialintelligence 

The paper presents some key lessons and "folk wisdom" that machine learning researchers and practitioners have learnt from experience and which are hard to find in textbooks. Representation for a learner is the set if classifiers/functions that can be possibly learnt. This set is called hypothesis space. If a function is not in hypothesis space, it can not be learnt. Evaluation function tells how good the machine learning model is.

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