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A curated list of programmatic weak supervision papers and resources
SPEAR: Programmatically label and build training data quickly.
Data Programming by Demonstration (DPBD) for Document Classification
Data programming by demonstration for information extraction and span annotation
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling
Code for the KDD-2023 paper: Neural-Hidden-CRF: A Robust Weakly-Supervised Sequence Labeler
Mongolian Polarity Detection in Weakly Supervised manner
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
A tool for automatically labelling discharge summaries into disease categories.
Source code of our ACL 2022 paper 'Learning to robustly aggregate labeling functions for semi-supervised data programming'
A curated list of awesome Weak-Supervision-Sequence-Labeling (WSSL) papers, methods & resources.
An approach to curating naturally adversarial datasets.
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.
F# tutorial: building applications, data programming and tests