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cleanlab
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
How about cleanlab? It works for any data you can train a classifier or get embeddings on (text, tabular, image, audio, etc). We just released some new features as well. Currently, cleanlab can automatically:
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CodeRabbit
CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
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refinery
The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.
You definitely forgot https://www.kern.ai/ :)
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grape
🍇 GRAPE is a Rust/Python Graph Representation Learning library for Predictions and Evaluations (by AnacletoLAB)
For graph embeddings, there's quite a few. I'd recommend this one, but there's also this one (disclaimer: I'm the author) or this one, more of a DGL library.
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For graph embeddings, there's quite a few. I'd recommend this one, but there's also this one (disclaimer: I'm the author) or this one, more of a DGL library.
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For graph embeddings, there's quite a few. I'd recommend this one, but there's also this one (disclaimer: I'm the author) or this one, more of a DGL library.
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Keras Tuner, Optuna : https://github.com/optuna/optuna ?
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awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
There is a cool, gigantic list for MLOps that I can recommend: https://github.com/EthicalML/awesome-production-machine-learning
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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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 paid product came out of an open source tool: https://github.com/snorkel-team/snorkel
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The deodel classifier can act as a quick dataset evaluation tool. If your data is available in table format, you can check its potential for prediction/classification. Just feed it to deodel. It accepts mixed attributes without any preliminary curation. It simply considers attribute values expressed as floats (dot decimal) as being continuous. It accepts even a mix of continuous and categorical values for the same attribute column.
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BotLibre
An open platform for artificial intelligence, chat bots, virtual agents, social media automation, and live chat automation.
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