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

Summary

In this chapter, you have learned the main options for getting started with AutoKeras, from installation to running in various environments.

You have also seen the power of AutoKeras by implementing two different approaches of a high-precision image classifier in just a few lines of code and 2 minutes of training.

Now that you have learned to implement a DL model from scratch, following these same steps and simply changing the dataset, your model would be able to classify all kinds of images.

In the following chapters, you will learn how to solve more complicated tasks related to images, structured data, and plaintext as input data sources, but before that, in the next chapter, we will see how to prepare the data to feed to AutoKeras by using some interesting tools to automate this process as much as possible.