Book Image

Machine Learning with BigQuery ML

By : Alessandro Marrandino
Book Image

Machine Learning with BigQuery ML

By: Alessandro Marrandino

Overview of this book

BigQuery ML enables you to easily build machine learning (ML) models with SQL without much coding. This book will help you to accelerate the development and deployment of ML models with BigQuery ML. The book starts with a quick overview of Google Cloud and BigQuery architecture. You'll then learn how to configure a Google Cloud project, understand the architectural components and capabilities of BigQuery, and find out how to build ML models with BigQuery ML. The book teaches you how to use ML using SQL on BigQuery. You'll analyze the key phases of a ML model's lifecycle and get to grips with the SQL statements used to train, evaluate, test, and use a model. As you advance, you'll build a series of use cases by applying different ML techniques such as linear regression, binary and multiclass logistic regression, k-means, ARIMA time series, deep neural networks, and XGBoost using practical use cases. Moving on, you'll cover matrix factorization and deep neural networks using BigQuery ML's capabilities. Finally, you'll explore the integration of BigQuery ML with other Google Cloud Platform components such as AI Platform Notebooks and TensorFlow along with discovering best practices and tips and tricks for hyperparameter tuning and performance enhancement. By the end of this BigQuery book, you'll be able to build and evaluate your own ML models with BigQuery ML.
Table of Contents (20 chapters)
Section 1: Introduction and Environment Setup
Section 2: Deep Learning Networks
Section 3: Advanced Models with BigQuery ML
Section 4: Further Extending Your ML Capabilities with GCP

Chapter 2: Setting Up Your GCP and BigQuery Environment

The first steps of using a new public cloud provider can be complex, and sometimes you might feel overwhelmed by all the services and options in front of you. Cloud vendors offer a vast variety of components and resources to solve different use cases. With this plethora of modules, it is not easy to decide which service to use. Fortunately, to create and run a Google Cloud Platform (GCP) project, you don't have to have specific technical skills or a large budget to invest. Regardless of whether you are a private user or an employee of a large company, GCP offers the possibility to use its cloud services simply by creating an account and a project on the platform. It is also possible to leverage a free trial to get credits and test products for a limited period of time.

The topics covered in this chapter will help to create a solid foundation for your technical environment, and the tasks covered should be performed only...