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

Chapter 12: Using BigQuery ML with AI Notebooks

For data scientists and machine learning engineers, notebooks are a fundamental productivity tool. Notebooks allow us to interact with computing resources because we can use them to write and execute code, visualize the results, and share the outcomes with other data scientists. Data engineers, data scientists, and machine learning engineers make experiments and explore data before deploying code into the production environment. They leverage notebooks because they offer a flexible and agile environment to develop and test in.

In this chapter, we'll learn what AI Platform Notebooks is, how to provision a notebook environment, and how to use it to develop a BigQuery ML model.

We'll start by discovering the basics of notebooks and then start getting some hands-on practice with Google Cloud Platform (GCP).

In this chapter, we'll cover the following topics: