5. Training your models

A deep learning project requires hundreds of models to be trained to iterate to the best one.

This is a logistical nightmare to handle, exacerbated by the technical complexities of dealing with the specialized hardware used for deep learning.

Expect to spend lots of time and resources on building and rebuilding tools for training models and managing trained models.

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