Summary
In this chapter, we have learned how to define Keras callbacks to monitor your models during training, how to use TensorBoard to view histograms, model graphs, and many more metrics besides, and how to monitor and track your experiments using the ClearML extension.
With these new tools, you will be better equipped to build your deep learning models in the real world and debug potential problems.
Throughout this book, we have learned the basic concepts necessary to use AutoKeras to solve any task based on text, images, or structured data, as well as the visualization techniques seen in this chapter. AutoKeras, Keras, and TensorFlow have excellent documentation that you can dig into for as long as you need. The foundations are already laid; now it's time to finish the building.
A final few words
This is the end of Automated Machine Learning with AutoKeras! I hope you have learned that it will help you to implement your own AI projects or to improve the ones you...