Three Ways to Build Machine Learning Models in Keras

If you’ve looked at Keras models on Github, you’ve probably noticed that there are some different ways to create models in Keras. There’s the Sequential model, which allows you to define an entire model in a single line, usually with some line breaks for readability. Then, there’s the functional interface that allows for more complicated model architectures, and there’s also the Model subclass which helps reusability. This article will explore the different ways to create models in Keras, along with their advantages and drawbacks. This will equip you with the knowledge you need to create your own machine learning models in Keras.

After you complete this tutorial, you will learn: