Book Image

Automated Machine Learning with AutoKeras

By : Luis Sobrecueva
Book Image

Automated Machine Learning with AutoKeras

By: Luis Sobrecueva

Overview of this book

AutoKeras is an AutoML open-source software library that provides easy access to deep learning models. If you are looking to build deep learning model architectures and perform parameter tuning automatically using AutoKeras, then this book is for you. This book teaches you how to develop and use state-of-the-art AI algorithms in your projects. It begins with a high-level introduction to automated machine learning, explaining all the concepts required to get started with this machine learning approach. You will then learn how to use AutoKeras for image and text classification and regression. As you make progress, you'll discover how to use AutoKeras to perform sentiment analysis on documents. This book will also show you how to implement a custom model for topic classification with AutoKeras. Toward the end, you will explore advanced concepts of AutoKeras such as working with multi-modal data and multi-task, customizing the model with AutoModel, and visualizing experiment results using AutoKeras Extensions. By the end of this machine learning book, you will be able to confidently use AutoKeras to design your own custom machine learning models in your company.
Table of Contents (15 chapters)
1
Section 1: AutoML Fundamentals
5
Section 2: AutoKeras in Practice
11
Section 3: Advanced AutoKeras

Exporting your models

The best model found by AutoKeras can be easily exported as a Keras model.

When saving your models to disk, this can be done in two different formats: the TensorFlow SavedModel format, and the older Keras H5 format. The recommended format is SavedModel, and this is the option used by default when we call to model.save().

How to save and load a model

Let's now see how to export and restore a model step by step:

  1. Export the model to a Keras model using the following code block:
    model = my_autokeras_model.export_model() 

    Now, try to save to the TensorFlow format using the h5 format as backup as something is wrong:

    try:
        model.save("model_autokeras", save_format="tf")
    except:
        model.save("model_autokeras.h5")
  2. Reload the model, as shown in the following code block:
    from tensorflow.keras.models import load_model
    loaded_model = load_model("model_autokeras", custom_objects...