Low-code ai. a practical project-driven introduction to machine learning, paperback/michael abel

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.

Youll learn key ML concepts by using real-world datasets with realistic problems.

Publisher: OReilly Media Author(s): Michael Abel Number of pages: 325 Publication date: 2023 Dimensions: 178 x 235 x 20 Cover type: Paperback / softback.