A system for quickly generating training data with weak supervision
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Updated
May 2, 2024 - Python
A system for quickly generating training data with weak supervision
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.
Code for the KDD-2023 paper: Neural-Hidden-CRF: A Robust Weakly-Supervised Sequence Labeler
Big Old Heuristic Repository
Mongolian Polarity Detection in Weakly Supervised manner
Code accompanying the TOP paper "Predicting the Demographics of Twitter Users with Programmatic Weak Supervision".
Process flow to generate labels on Text data using Snorkel and maintain DB to repurpose unlabelled data
"Snorkel with Turtle" is a realtime labeling system based on Snorkel
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.
This is a POC project of a system that aim to label unlabeled streaming data using Snorkel
Snorkel MeTaL: A framework for training models with multi-task weak supervision
Weak Labeling of Fake News Articles with Snorkel and Snuba
Interactive Label Generation Tool for Time Series Data
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