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

Discovering the relationship between BigQuery ML and TensorFlow

In this section, we'll understand the relationship between BigQuery ML and TensorFlow. After completing this section, we'll be able to understand when to use BigQuery ML and TensorFlow according to our use case, but also how to get the best out of the two technologies, when they're used together.

Understanding commonalities and differences

BigQuery ML and TensorFlow have some similar aspects, but there are also some relevant differences to highlight.

In the following table, we have summarized the main similarities and differences of these two frameworks:

Figure 13.1 – Comparing BigQuery ML and TensorFlow

First, it is important to underline that TensorFlow offers greater flexibility in terms of the ML models that can be implemented. While BigQuery ML is characterized by a specific list of supported model types (https://cloud.google.com/bigquery-ml/docs/introduction...