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

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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 1: Introduction to Google Cloud and BigQuery

The adoption of the public cloud enables companies and users to access innovative and cost-effective technologies. This is particularly valuable in the big data and Artificial Intelligence (AI) areas, where new solutions are providing possibilities that seemed impossible to achieve with on-premises systems only a few years ago. In order to be effective in the day-to-day business of a company, the new AI capabilities need to be shared between different roles and not concentrated only with technicians. Most cloud providers are currently addressing the challenge of democratizing AI across different departments and employees with different skills.

In this context, Google Cloud provides several services to accelerate the processing of large amounts of data and build Machine Learning (ML) applications that can make better decisions.

In this chapter, we'll gradually introduce the main concepts that will be useful in the upcoming hands-on activities. Using an incremental approach, we'll go through the following topics: