October 2017
Beginner to intermediate
270 pages
7h
English
Content preview from Machine Learning for Developers
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Dataset partitioning
At the time of training the models, we usually partition all the provided data into three sets: the training set, which will actually be used to adjust the parameters of the models; the validation set, which will be used to compare alternative models applied to that data (it can be ignored if we have just one model and architecture in mind); and the test set, which will be used to measure the accuracy of the chosen model. The proportions of these partitions are normally 70/20/10.
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