PinnedPiero MolinoIntroducing Predibase: the enterprise declarative machine learning platformPlaceholderMay 18, 2022May 18, 2022
Abhay MalikPredicting Customer Reviews with Multi-Modal Machine LearningPredicting Customer Review Ratings on Multi-Modal Data with Predibase and LudwigMar 13, 2023Mar 13, 2023
Michael Ortega10 AI Predictions that Will Shape 2023 and BeyondPredictions from ML industry experts with experience at Uber, Google, Amazon Web Services (AWS), Databricks and the open-source community.Jan 30, 2023Jan 30, 2023
Joppe GeluykensBoost Tabular Data Predictions with Tree Models in Ludwig 0.6Ludwig, the open-source declarative ML framework, now supports gradient boosted tree models (GBM) in addition to neural networks (NN).Jan 4, 2023Jan 4, 2023
GeoffreyHow to Run Inference on Ludwig Models Using TorchScriptLudwig now makes it even easier to deploy models for highly performant inference with TorchScript.Dec 20, 2022Dec 20, 2022
Jim ThompsonUnit Testing Machine Learning Code in Ludwig and PyTorch: Tests for Gradient UpdatesEditors: Justin Zhao, Daniel Treiman, Piero MolinoOct 27, 2022Oct 27, 2022
Abhay MalikDeclarative Machine Learning and the Future of Data ScienceABSTRACT: Declarative ML has the potential to reduce the time, effort, and skills required to bring ML into production in a wide range of…Oct 18, 2022Oct 18, 2022
Justin ZhaoLudwig v0.6 — Gradient Boosted Models, Schema Validation, and Pipelined TorchScriptOverviewOct 5, 20221Oct 5, 20221
Justin ZhaoLudwig 0.5: Declarative Machine Learning, now on PyTorchLudwig 0.5 is a complete renovation of Ludwig with a focus on parity, scalability, deployment, reliability, and documentation.Jun 29, 2022Jun 29, 2022
Anne HollerLudwig AutoML for Text ClassificationAuthors: Anne Holler, Justin Zhao, Avanika Narayan,Travis Addair, Devvret Rishi, Piero MolinoMay 3, 2022May 3, 2022