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hey youtube itamp;#39;s dmitry and today weamp;#39;re going to talk about cross validation weamp;#39;re going to talk specifically about cross validation failure because i see this constantly in the industry and we get this really nice warm cozy feeling that things are gonna work and then magically they donamp;#39;t work because we didnamp;#39;t understand whatamp;#39;s going on with this so letamp;#39;s just dive on in uh what is cross-validation so cross-validation is an out-of-sample method for testing how well a model is going to perform on independent data now this doesnamp;#39;t give us an exact metric it doesnamp;#39;t mean if i pass this it will have flying colors in practice which weamp;#39;re going to see here in a second but it gives us an indication that okay when new data comes in that the model has not seen it should perform fairly well here today weamp;#39;re going to talk specifically about k-fold cross-validation k-fold just indicates the number of partition
