ML Infra + Apps

Predibase: A low-code deep learning platform built for scale

Wednesday, August 24
1:15 PM - 1:45 PM

Predibase is a new kind of low-code machine learning platform from the creators of Ludwig and Horovod, combining large-scale deep learning with state-of-the-art model architectures across a range of modalities, including NLP, computer vision, tabular, and hybrid data. Unlike existing AutoML solutions, Predibase provides a modular "lego brick" experience that allows data scientists and engineers alike to iteratively build the best model for their data without needing to master a low-level framework like PyTorch or TensorFlow. In this talk, we'll explain how Predibase uses Ludwig and Ray under the hood to deliver an end-to-end, cloud-native solution encompassing data processing, model training, hyperparameter optimization, and model serving, all done at scale. We'll also explore how Predibase provides a unique serverless abstraction over Ray, allowing us to support multi-cloud and multi-tenant deployments capable of handling many concurrent users and requests.

About Travis

Travis Addair is co-founder and CTO of Predibase, a data-oriented low-code machine learning platform. Within the Linux Foundation, he serves as lead maintainer for the Horovod distributed deep learning framework and is a co-maintainer of the Ludwig automated deep learning framework. In the past, he led Uber's deep learning training team as part of the Michelangelo machine learning platform.

Travis Addair

Chief Technology Officer, Predibase Inc.
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