refinery-sample-projects
git-bruh
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refinery-sample-projects | git-bruh | |
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3 | 1 | |
23 | 0 | |
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0.0 | 2.8 | |
9 months ago | about 1 month ago | |
Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
refinery-sample-projects
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How to fine-tune your embeddings for better similarity search
This blog post will share our experience with fine-tuning sentence embeddings on a commonly available dataset using similarity learning. We additionally explore how this could benefit the labeling workflow in the Kern AI refinery. To understand this post, you should know what embeddings are and how they are generated. A rough idea of what fine-tuning is also helps. All the code and data referenced in this post is available on GitHub.
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Build your own stock sentiment classifier with Kern Refinery (video series)
Repository of the sample use case for the UI elements (optional).
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Show HN: If VS Code had a data-centric IDE sibling, what would that look like?
Hey, I'm Johannes - one of the maintainers of refinery. Thanks Jonathan for sharing!!
Would be super excited if you guys have any feedback. It's nowhere near perfect yet, but you can already use it to build some great data-centric use cases. Amongst others for sentiment analysis, conversational AI or finetuning of your embeddings (which you can check out here: https://github.com/code-kern-ai/refinery-sample-projects).
Let me know what you think :)
git-bruh
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Show HN: If VS Code had a data-centric IDE sibling, what would that look like?
This project's README reminds me of git-bruh's GitHub page: https://github.com/git-bruh/git-bruh/blob/main/README.md
I'm sorry, I just can't think of anything else anymore when I hear the word "microservices". This is the most sane use of them I've seen yet, so there's that.
What are some alternatives?
refinery - The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.
automl-docker - CLI-based tool to automatically build ML models from training data into a servable Docker container
azuredatastudio - Azure Data Studio is a data management and development tool with connectivity to popular cloud and on-premises databases. Azure Data Studio supports Windows, macOS, and Linux, with immediate capability to connect to Azure SQL and SQL Server. Browse the extension library for more database support options including MySQL, PostgreSQL, and MongoDB.
Owlie - Owlie est un chatbot de soutien psychologique gratuit, disponible 24h/24 et 7j/7