snorkel
dcai-lab

snorkel | dcai-lab | |
---|---|---|
6 | 10 | |
5,828 | 440 | |
0.0% | 0.0% | |
5.2 | 5.4 | |
10 months ago | about 1 year ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | GNU Affero General Public License v3.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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snorkel
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Harnessing Weak Supervision to Isolate Sign Language in Crowded News Videos
Hello everyone, we are trying to make a large dataset for Sign Language translation, inspired by BSL-1K [1]. As part of cleaning our collected videos, we use a nice technique for aggregating heuristic labels [2]. We thought it was interesting enough to share with people on here.
[1] https://www.robots.ox.ac.uk/~vgg/research/bsl1k/
[2] https://github.com/snorkel-team/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:
dcai-lab
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Resources to learn practical/industry-focused ML (preferably using TensorFlow)?
Data-Centric AI honestly if you've been working on ML pipelines this might be familiar to you
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Andrew NG, github courses
Another great resource inspired by the Andrew Ng data-centric AI movement is the Introduction to Data-Centric AI course taught this past semester at MIT by PhDs.
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Good Beginner Courses for ML?
Data-centric AI course. Brand new, taught the 1st time a few months ago by MIT PhD grads. This covers how to ensure good data quality for your models. More data science havy.
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[P] We are building a curated list of open source tooling for data-centric AI workflows, looking for contributions.
Thanks for the kind words! Make sure to check out the current open MIT course if you are just starting out: https://dcai.csail.mit.edu/
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The Missing Semester of Your CS Education
Introduction to Data-Centric AI https://dcai.csail.mit.edu
- Introduction to Data-Centric AI
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MIT Introduction to Data-Centric AI
Course homepage | Lecture videos on YouTube | Lab Assignments
What are some alternatives?
cleanlab - The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
deodel - A mixed attributes predictive algorithm implemented in Python.
argilla - Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
nodevectors - Fastest network node embeddings in the west
skweak - skweak: A software toolkit for weak supervision applied to NLP tasks
UBB-INFO - All projects from university.
weasel - Weakly Supervised End-to-End Learning (NeurIPS 2021)
BotLibre - An open platform for artificial intelligence, chat bots, virtual agents, social media automation, and live chat automation.
spaCy - đź’« Industrial-strength Natural Language Processing (NLP) in Python
llm-course - Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
dcai-course - Introduction to Data-Centric AI, MIT IAP 2023 🤖
