How to Use AutoKeras for Classification and Regression

Last Updated on September 6, 2020

AutoML refers to techniques for automatically discovering the best-performing model for a given dataset.

When applied to neural networks, this involves both discovering the model architecture and the hyperparameters used to train the model, generally referred to as neural architecture search.

AutoKeras is an open-source library for performing AutoML for deep learning models. The search is performed using so-called Keras models via the TensorFlow tf.keras API.

It provides a simple and effective approach for automatically finding top-performing models for a wide range of predictive modeling tasks, including tabular or so-called structured classification and regression datasets.

In this tutorial, you will discover how to use AutoKeras to find good neural network models for classification and regression tasks.

After completing this tutorial, you will know:

• AutoKeras is an implementation of AutoML for deep learning that uses neural architecture search.
• How to use AutoKeras to find a top-performing model for a binary classification dataset.
• How to use AutoKeras to find a top-performing model for a regression dataset.

Let’s get started.

• Update Sep/2020: Updated AutoKeras version and installation instructions.

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