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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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Toc

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 11: Implementing Deep Neural Networks

Deep Neural Networks (DNNs) are one of the most advanced techniques to implement machine learning algorithms. They're widely used for different use cases and can be considered pervasive in everyday life.

When we interact with a virtual assistant, or we use mobile applications for automatic translation and image recognition, we're leveraging the capabilities of DNNs trained with large datasets of audio and images.

After reading this chapter, you'll be able to develop, evaluate, and test a DNN using BigQuery ML. In this chapter, we'll see all the stages necessary to implement a DNN by using BigQuery ML to predict the duration of rentals related to the New York City bike-sharing service.

Using BigQuery ML, we'll go through the following topics:

  • Introducing the business scenario
  • Discovering DNNs
  • Preparing the dataset
  • Training the DNN models
  • Evaluating the DNN models
  • Using the DNN...
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