Low-Code AI: A Practical Project-Driven Introduction to Machine Learning

Take a data-first and use-case driven approach to understanding machine learning and deep learning concepts with Low-Code AI. This hands-on guide presents three problem-focused ways to learn ML: no code using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. You'll learn key ML concepts by using real-world datasets with realistic problems.

Business and data analysts get a project-based introduction to ML/AI using a detailed, data-driven approach: loading and...