Once you have a trained model for your deep learning experiment, what do you do to improve its performance?
As I discuss in the video, there are a couple of tactics that one could implement. And I'll briefly mention some of them:
- you could train the model for longer
- you could do the training on better hardware
- you could increase the size of the model
- you could implement data augmentation procedures
- you could focus a lot on preprocessing and optimization
- etc.
For a breakdown on each of these, in more detail, please see the video lesson below.
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Cristi Vlad Self-Experimenter and Author