Low-Code AI

Low-Code AI A Practical Project-Driven Introduction to Machine Learning is a book written by Gwendolyn Stripling and Michael Abel. The book provides a data-first and use-case-driven approach to understanding machine learning and deep learning concepts. It presents three problem-focused ways to learn machine learning: no-code ML using AutoML, low-code using BigQuery ML, and custom code using sci-kit-learn and Keras.