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 8: Topic Classification Using AutoKeras

Sometimes, we need to categorize some specific text, such as a product or movie review, into one or more categories by assigning tags or topics. Topic classification is a supervised machine learning technique that does exactly this job: predicting which categories a given text belongs to. Being a supervised model, it needs to be trained with a set of already categorized train data, along with the texts and the categories that each one belongs to.

This chapter will be mainly practical since we laid the foundations for text-based tasks in previous chapters. By the end of this chapter, you will have learned how to create a topic classifier with AutoKeras, as well as how to apply it to any topic or category-based dataset.

The main topics that will be covered in this chapter are as follows:

  • Understanding topic classification
  • Creating a topic classifier with AutoKeras
  • Customizing the model search space

First...