What this book covers
Chapter 1, Introduction to Google Cloud and BigQuery, provides an overview of the Google Cloud Platform and of the BigQuery analytics database.
Chapter 2, Setting Up Your GCP and BigQuery Environment, explains the configuration of your first Google Cloud account, project, and BigQuery environment.
Chapter 3, Introducing BigQuery Syntax, covers the main SQL operations for working on BigQuery.
Chapter 4, Predicting Numerical Values with Linear Regression, explains the development of a linear regression ML model to predict the trip durations of a bike rental service.
Chapter 5, Predicting Boolean Values Using Binary Logistic, explains the implementation of a binary logistic regression ML model to predict the behavior of a taxi company's customers.
Chapter 6, Classifying Trees with Multiclass Logistic Regression, explains the development of a multiclass logistic ML algorithm to automatically classify species of trees according to their natural characteristics.
Chapter 7, Clustering Using the K-Means Algorithm, covers the implementation of a clustering system to identify the best-performing drivers in a taxi company.
Chapter 8, Forecasting Using Time Series, outlines the design and implementation of a forecasting tool to predict and present the sales of specific products.
Chapter 9, Suggesting the Right Product by Using Matrix Factorization, explains how to build a recommendation engine, using the matrix factorization algorithm, that suggests the best product to each customer.
Chapter 10, Predicting Boolean Values Using XGBoost, covers the implementation of a boosted tree ML model to predict the behavior of a taxi company's customers.
Chapter 11, Implementing Deep Neural Networks, covers the design and implementation of a Deep Neural Network (DNN) to predict the trip durations of a bike rental service.
Chapter 12, Using BigQuery ML with AI Notebooks, explains how AI Platform Notebooks can be integrated with BigQuery ML to develop and share ML models.
Chapter 13, Running TensorFlow Models with BigQuery ML, explains how BigQuery ML and TensorFlow can work together.
Chapter 14, BigQuery ML Tips and Best Practices, covers ML best practices and tips that can be applied during the development of a BigQuery ML model.