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Your model can score perfectly on training data and still fail completely on new data. That's overfitting — and Slides available at: cs.ox.ac.uk/people/nando.defreitas/machinelearning/ Course taught in 2015 at the University of ... 00:00 Introduction 01:10 Managing Complexity 06:57 Right so NCP seems to work very nice for this particular test problem his d cv g cv tends to produce a Your network hits 99% training accuracy and 70% validation accuracy. That's not success — that's memorisation. This
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