Neural Networks and TensorFlow - Deep Learning Series [Part 24]

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.

To stay in touch with me, follow @cristi

Cristi Vlad Self-Experimenter and Author