Piero Molino·PinnedIntroducing Predibase: the enterprise declarative machine learning platformA high performance, low-code approach to machine learning for data practitioners and engineers For the last year, we’ve quietly been building Predibase — the first enterprise declarative machine learning platform. Under a common belief that ML shouldn’t be so hard to implement in the enterprise, the founding team came together…Machine Learning9 min read
Anne Holler·May 3Ludwig AutoML for Text ClassificationAuthors: Anne Holler, Justin Zhao, Avanika Narayan,Travis Addair, Devvret Rishi, Piero Molino INTRODUCTION Ludwig is an open-source declarative deep learning (DL) framework that enables individuals from a variety of backgrounds to train and deploy state-of-the-art tabular, natural language processing, and computer vision models. Ludwig is a toolkit for end-to-end machine learning…Deep Learning15 min read
Anne Holler·Feb 15Ludwig AutoML for Deep LearningAuthors: Anne Holler, Avanika Narayan, Justin Zhao, Shreya Rajpal, Daniel Treiman, Devvret Rishi, Travis Addair, Piero Molino INTRODUCTION Ludwig is an open-source declarative deep learning (DL) framework that enables individuals from a variety of backgrounds to train and deploy state-of-the-art tabular, natural language processing, and computer vision models. Ludwig serves as…Deep Learning11 min read
Piero Molino·Jun 15, 2021Ludwig AI v0.4 — Introducing Declarative MLOps with Ray, Dask, TabNet, and MLflow integrationsAuthors: Piero Molino, Travis Addair, Devvret Rishi We’re excited to announce the availability of Ludwig version 0.4 — the open source, low-code declarative deep learning framework created and open sourced by Uber and hosted by the LF AI & Data Foundation. …Machie Learning11 min read
Kanishk Kalra·Feb 25, 2021The Complete Guide To Sentiment Analysis with Ludwig — Part IIThis is Part 2 of a 3-part series to The Complete Guide To Sentiment Analysis with Ludwig. Part 1 shows how to load the dataset and how to obtain baseline Ludwig models. This part will show how to work with Transformer encoders like BERT and how to compare all the…NLP6 min read
Kanishk Kalra·Feb 25, 2021The Complete Guide to Sentiment Analysis with Ludwig —Part IA 3-part guide to go from importing dataset and implementing baseline models to working with BERT and doing Hyperparameter Optimization, all using only Ludwig. You can follow along with the code through the Colab notebook. Authors: Kanishk Kalra, Michael Zhu, Elias Castro Hernandez, and Piero Molino Thanks to Debbie Yuen…NLP9 min read
Michael Zhu·Dec 22, 2020The Complete Guide to Sentiment Analysis with Ludwig — Part III: Hyperparameter OptimizationThis is the third article of a 3-part series about using Ludwig to perform Sentiment Analysis on the Stanford Sentiment Treebank dataset. Part 1 provides an introduction to the dataset and shows how to train two types of models (Bi-LSTM and parallel-CNN). Part 2 describes the BERT model and how…Deep Learning7 min read
