You're reading from Machine Learning with BigQuery ML Create, execute, and improve machine learning models in BigQuery using standard SQL queries

Product type Paperback

Published in Jun 2021

Publisher Packt

ISBN-13 9781800560307

Length 344 pages

Edition 1st Edition

Languages

Python

Tools

BigQuery

Concepts

Machine Learning

Author (1):

Alessandro Marrandino

View More author details

Table of Contents (20) Chapters

Preface

1. Section 1: Introduction and Environment Setup

2. Chapter 1: Introduction to Google Cloud and BigQuery FREE CHAPTER

3. Chapter 2: Setting Up Your GCP and BigQuery Environment

4. Chapter 3: Introducing BigQuery Syntax

5. Section 2: Deep Learning Networks

6. Chapter 4: Predicting Numerical Values with Linear Regression

7. Chapter 5: Predicting Boolean Values Using Binary Logistic Regression

8. Chapter 6: Classifying Trees with Multiclass Logistic Regression

9. Section 3: Advanced Models with BigQuery ML

10. Chapter 7: Clustering Using the K-Means Algorithm

11. Chapter 8: Forecasting Using Time Series

12. Chapter 9: Suggesting the Right Product by Using Matrix Factorization

13. Chapter 10: Predicting Boolean Values Using XGBoost

14. Chapter 11: Implementing Deep Neural Networks

15. Section 4: Further Extending Your ML Capabilities with GCP

16. Chapter 12: Using BigQuery ML with AI Notebooks

17. Chapter 13: Running TensorFlow Models with BigQuery ML

18. Chapter 14: BigQuery ML Tips and Best Practices

19. Other Books You May Enjoy

Creating your GCP account and project

The first step to start using GCP is the creation of a new GCP account and a new project. A project is a container of multiple GCP resources, and it is usually accessed by users through their accounts. Examples of GCP resources include Google Compute Engine VMs, Google Cloud Storage buckets, App Engine instances, and BigQuery datasets. A GCP project is also linked to a billing account to which all of the costs of services consumption are charged. GCP objects can be organized hierarchically. Projects are the first level of the hierarchy and can be grouped into folders. Each folder can have another folder or an organization node as a parent. The organization is at the top of the GCP hierarchy and cannot have a parent.

In the following diagram, you can see a hierarchy composed of an organization node, two main folders, and two nested folders linked to three different GCP projects:

Figure 2.1 – GCP resource hierarchy...