[NeurIPS 2021] WRENCH: Weak supeRvision bENCHmark

A curated list of programmatic weak supervision papers and resources

SPEAR: Programmatically label and build training data quickly.

Data programming by demonstration for information extraction and span annotation

Data Programming by Demonstration (DPBD) for Document Classification

Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling

Source code for the CSE 163: Intermediate Data Programming book (with code for practice problems)

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

Mongolian Polarity Detection in Weakly Supervised manner

A tool for automatically labelling discharge summaries into disease categories.

This repository contains source code of our ACL 2021 paper **Data Programming using Semi-Supervision and Subset Selection**

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

Source code of our ACL 2022 paper 'Learning to robustly aggregate labeling functions for semi-supervised data programming'

An approach to curating naturally adversarial datasets.

A curated list of awesome Weak-Supervision-Sequence-Labeling (WSSL) papers, methods & resources.

Prepare a data set based on the model that you already have, then experiment with 'training' your 'Machine Learning' tool on this data. Did it recognize the model? Sorry, that was a stupid question. Why didn't it? You can find out with the help of these tools here.

One common repo for all of my R projects

F# tutorial: building applications, data programming and tests