Introduction

Keras is one of the most popular go-to Python libraries/APIs for beginners and professionals in deep learning. Although it started as a stand-alone project by François Chollet, it has been integrated natively into TensorFlow starting in Version 2.0. Read more about it here.

As the official doc says, it is “an API designed for human beings, not machines” as it “follows best practices for reducing cognitive load”.

Image source: Pixabay

One of the situations, where the cognitive load is sure to increase, is hyperparameter tuning. Although there are so many supporting libraries and frameworks for handling it, for simple grid searches, we can always rely on some built-in goodies in Keras.

In this article, we will quickly look at one such internal tool and examine what we can do with it for hyperparameter tuning and search.

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