snorkel-tutorials
snorkel
| snorkel-tutorials | snorkel | |
|---|---|---|
| 1 | 5 | |
| 376 | 5,712 | |
| 0.8% | 0.5% | |
| 0.0 | 5.5 | |
| about 1 month ago | 2 months ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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snorkel-tutorials
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Can't use load_data from utils
I see load_data in spouse.utils https://github.com/snorkel-team/snorkel-tutorials/blob/master/spouse/utils.py
snorkel
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[P] We are building a curated list of open source tooling for data-centric AI workflows, looking for contributions.
The paid product came out of an open source tool: https://github.com/snorkel-team/snorkel
- [Discussion] - "data sourcing will be more important than model building in the era of foundational model fine-tuning"
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Can't use load_data from utils
Actually, I referenced it in my issue as well. There seems to be different utils.py file in different folders under the snorkel-tutorials repo but the utils file we get after importing snorkel has a different [file](https://github.com/snorkel-team/snorkel/blob/master/snorkel/utils/core.py) ,i.e. the utils file is different in the main snorkel repo
- [D] A hand-picked selection of the best Python ML Libraries of 2021
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[Discussion] Methods for enhancing high-quality dataset A with low-quality dataset
Snorkel (https://github.com/snorkel-team/snorkel) might provide you exactly what you are looking for. From the docs:
What are some alternatives?
skweak - skweak: A software toolkit for weak supervision applied to NLP tasks
argilla - Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
weasel - Weakly Supervised End-to-End Learning (NeurIPS 2021)
caer - High-performance Vision library in Python. Scale your research, not boilerplate.
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
cleanlab - The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
dgl - Python package built to ease deep learning on graph, on top of existing DL frameworks.
awesome-production-machine-learning - A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
dcai-lab - Lab assignments for Introduction to Data-Centric AI, MIT IAP 2024 👩🏽💻
BotLibre - An open platform for artificial intelligence, chat bots, virtual agents, social media automation, and live chat automation.