BigQuery ML Tutorial: Step-by-Step Guide With Examples (2024)

• 11/2/2024
• One-minute read

Complete BigQuery ML Tutorial

Quick Start Guide

1. Prerequisites
   • Google Cloud account
   • BigQuery access
   • Sample dataset

Getting Started with BigQuery ML

Model Types Available

Basic Model Creation

CREATE OR REPLACE MODEL `project.dataset.churn_model`
OPTIONS(
  model_type='logistic_reg',
  input_label_cols=['churned']
) AS
SELECT
  churned,
  tenure,
  monthly_charges,
  total_charges,
  contract_type
FROM
  `project.dataset.customer_data`
WHERE
  churned IS NOT NULL;

Model Evaluation

SELECT
  *
FROM
  ML.EVALUATE(MODEL `project.dataset.churn_model`);

Best Practices

1. Data Preparation

   • Handle missing values
   • Normalize features
   • Split train/test data

2. Model Optimization

   • Use early stopping
   • Implement cross-validation
   • Monitor training metrics

Resources

• BigQuery ML Documentation
• Model Reference
• SQL Functions

Note: Features and syntax are current as of February 2024. Check documentation for updates.