Hello again! In the last lesson, we looked at training and testing. We saw that we can evaluate a classifier on an independent test set, or using a percentage split, with a certain percentage of the dataset used to train and the rest used for testing, or — and this is generally a very bad idea — we can evaluate it on the training set itself, which gives misleadingly optimistic performance figures. In this lesson, we’re going to look a little bit more at training and […]

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