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Training is the part of machine learning whereby a model is "trained" on a define portion of a dataset to learn attributes and statistical features of the data. It's counterparts are called Testing and Validation. After training a model is tested and validated on another portion of the dataset.

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Potential problems with expanding training set

For example, a common practice when training models such as CNNs on images is to perform data augmentation by rotating/scaling the initial images. …
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