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

Introducing TensorFlow

In this section, we'll introduce TensorFlow, its origins, and what this framework has achieved in the ML community.

TensorFlow is an open source library that's used to develop ML models. It's very flexible and can be used to address a wide variety of use cases and business scenarios. Since TensorFlow is based on math functions, its name comes from the mathematical concept of the Tensor.

In math, a Tensor is an algebraic object that describes a relationship between sets of other algebraic objects. Some examples of tensors are vectors and matrixes.

The TensorFlow library was originally created by Google's engineers and then released under the Apache License in 2015. Now, it is recognized as one of the most popular ML frameworks due to its potential and flexibility. In fact, a TensorFlow model can be executed on local machines, on-premises servers, in the cloud, or at the edge, such as on mobile phones and video surveillance cameras...