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• Most functions and methods in fastai that return a collection use a class called L. L can be thought of as an enhanced version of the ordinary Python list type, with added conveniences for common operations.
• Once you think your data looks right, we generally recommend the next step should be using it to train a simple model
• works even when our dependent variable has more than two categories.
• To actually get a batch of real data from our DataLoaders, we can use the one_batch method:
• Note that it may be less ideal during inference, as you might want your model to sometimes tell you it doesn’t recognize any of the classes that it has seen during training, and not pick a class because it has a slightly bigger activation score. In this case, it might be better to train a model using multiple binary output columns, each using a sig...

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