A Coding Guide to Build a Scalable End-to-End Machine Learning Data Pipeline Using Daft for High-Performance Structured and Image Data Processing
In this tutorial, we explore how we use Daft as a high-performance, Python-native data engine to build an end-to-end analytical pipeline. We start by loading a real-world MNIST dataset, then progressively transform it using UDFs, feature engineering, aggregations, joins, and lazy execution. Also, we demonstrate how to seamlessly combine structured data processing, numerical computation, and […]
