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 13: Running TensorFlow Models with BigQuery ML

TensorFlow is one of the most used and relevant Machine Learning (ML) frameworks available. It allows data scientists and ML engineers to develop advanced models, and it also provides great flexibility and a rich set of mathematical functions.

The advanced features that TensorFlow offers provide a huge opportunity for data analysts that want to leverage existing models developed by data scientists and ML engineers.

Furthermore, the interoperability between BigQuery ML and TensorFlow represents a way to fill the gap between business and technical stakeholders within companies. The first group is usually more focused on in-depth knowledge of the data, while the second is technical-oriented and focused on programming skills.

In this chapter, we'll learn what TensorFlow is and how it can be used with BigQuery ML. We'll understand how to export a BigQuery ML model into the TensorFlow format and how to run TensorFlow...