You're reading from Automated Machine Learning Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms

Product type Paperback

Published in Feb 2021

Publisher Packt

ISBN-13 9781800567689

Length 312 pages

Edition 1st Edition

Languages

Python

Tools

Azure Functions

Concepts

Machine Learning

Author (1):

Adnan Masood

View More author details

Table of Contents (15) Chapters

Preface

1. Section 1: Introduction to Automated Machine Learning

2. Chapter 1: A Lap around Automated Machine Learning FREE CHAPTER

3. Chapter 2: Automated Machine Learning, Algorithms, and Techniques

4. Chapter 3: Automated Machine Learning with Open Source Tools and Libraries

5. Section 2: AutoML with Cloud Platforms

6. Chapter 4: Getting Started with Azure Machine Learning

7. Chapter 5: Automated Machine Learning with Microsoft Azure

8. Chapter 6: Machine Learning with AWS

9. Chapter 7: Doing Automated Machine Learning with Amazon SageMaker Autopilot

10. Chapter 8: Machine Learning with Google Cloud Platform

11. Chapter 9: Automated Machine Learning with GCP

12. Section 3: Applied Automated Machine Learning

13. Chapter 10: AutoML in the Enterprise

14. Other Books You May Enjoy

Automated machine learning for price prediction

So far, you have seen how AutoML Tables can be used for classification problems; that is, finding classes in a dataset. Now, let's do some regression; that is, predicting values. To do this, we will use the house sales prediction dataset. The King County house sales dataset contains prices for King County, which includes Seattle. The dataset can be downloaded from Kaggle at https://www.kaggle.com/harlfoxem/housesalesprediction.

For this experiment, our goal is to predict a house's sale value (price) by using 21 features and 21,613 observations or data points:

Let's start in AI Platform by clicking on the CREATE DATASET button on the main page:
Figure 9.34 – AutoML Tables – getting started with the AI Platform home page
Here, you must choose a dataset name and region, as shown in the following screenshot. Set the dataset's type to tabular since it currently has classification and regression automated...