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

Chapter 9: Working with Multimodal and Multitasking Data

In this chapter, we will learn how to use the AutoModel API to handle multimodal and multitasking data.

By the end of this chapter, you will have learned how to use the concepts and tools necessary to create models with multiple inputs and multiple outputs. You will be able to apply these concepts to your own projects by creating a model from scratch or by adapting the practical example shown in this chapter to other, similar datasets.

In this chapter, we will cover the following topics:

  • Exploring models with multiple input or outputs
  • Creating a multitasking/multimodal model
  • Customizing the search space

But first, let's explain the technical requirements for this chapter.