Ludwig is a code-free deep learning toolbox based on TensorFlow open-sourced by Uber AI Labs. Ludwig is unique in its ability to help make deep learning easier to understand for non-experts and enable faster model development cycles for experienced machine learning developers and researchers alike. By using Ludwig, experts and researchers can simplify the prototyping process and streamline data processing so that they can focus on developing deep learning architectures rather than wrangling data.
Ludwig introduces the notion of data-type-specific encoders and decoders, which results in a highly modularized and extensible architecture: each type of data supported (text, images, categories, and so on) has a specific preprocessing function.
In this talk, we’ll be looking at leveraging TensorFlow -Extended (TFX) pipelines to programmatically create Deep Learning models with Ludwig for different input data types for both model training and inference using Beam-Flink-Python SDK.
Suneel is a Member of Apache Software Foundation. He's previously presented at Flink Forward Berlin, Hadoop Summit Europe, Berlin Buzzwords, Open Source Summit, Big Data Tech Warsaw, and Beam Summit in the past.
Wednesday October 30, 2019 11:30 - 12:05 CET
Rhone 1
