A system for quickly generating training data with weak supervision

Extracting biomedical relationships from literature with Snorkel 🏊

A PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.

Retrieve and process PubTator annotations

Big Old Heuristic Repository

Jupyter book showing how to build an ML powered book genre classifier

Unsupervised tableQA and databaseQA on chinese finance question and tabular data

Process flow to generate labels on Text data using Snorkel and maintain DB to repurpose unlabelled data

Code for the KDD-2023 paper: Neural-Hidden-CRF: A Robust Weakly-Supervised Sequence Labeler

Snorkel MeTaL: A framework for training models with multi-task weak supervision

In this project, we are using Snorkel Python to work with ML algorithms with an unlabeled text dataset.

Convertir máscara Snorkel a CPAP y a máscara de Equipo de Prevención Individual (EPIs)

Utilizing the snorkel machine learning model to label biomimicry papers. Snorkel uses weak supervision to label large amounts of training data using programmatic labeling functions based on keyword rules.

AbusiveLanguage2020 is an open source dataset with over 1.5M tweets labeled for abusive language.

Mongolian Polarity Detection in Weakly Supervised manner

Labelling dataset with Snorkel and TextBlob, building model with Scikit-Learn (SVM), wiring up a web app using Flask.

Code accompanying the TOP paper "Predicting the Demographics of Twitter Users with Programmatic Weak Supervision".

Semi-supervised labelling of news snippets to extract cleantech news