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Machine Learning with BigQuery ML

You're reading from   Machine Learning with BigQuery ML Create, execute, and improve machine learning models in BigQuery using standard SQL queries

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Product type Paperback
Published in Jun 2021
Publisher Packt
ISBN-13 9781800560307
Length 344 pages
Edition 1st Edition
Languages
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Author (1):
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Alessandro Marrandino Alessandro Marrandino
Author Profile Icon Alessandro Marrandino
Alessandro Marrandino
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Table of Contents (20) Chapters Close

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 9: Suggesting the Right Product by Using Matrix Factorization

Suggesting the right product is one of the most common applications of Machine Learning (ML). Every day, product recommendation systems influence our choices on the internet. Newsletters, e-commerce websites, video streaming companies, and many other services leverage this powerful ML technique to offer us meaningful suggestions about the products that we may buy or like.

In this chapter, with a hands-on and practical approach, we'll execute the main implementation steps to build a new recommendation engine using the matrix factorization algorithm.

With a gradual and incremental approach and by leveraging BigQuery ML, we'll cover the following topics:

  • Introducing the business scenario
  • Discovering matrix factorization
  • Configuring BigQuery Flex Slots
  • Exploring and preparing the dataset
  • Training the matrix factorization model
  • Evaluating the matrix factorization model
  • ...
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