fides
dvc
fides | dvc | |
---|---|---|
2 | 110 | |
328 | 13,189 | |
0.6% | 1.0% | |
9.8 | 9.6 | |
6 days ago | 1 day ago | |
Python | Python | |
Apache License 2.0 | 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.
fides
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What data governance tool are you folks using?
I’ve also been impressed with the approach of Fides, an open source privacy management framework that ties into ci/cd, though I haven’t used it myself yet. The thing about it that stood out was Fideslang, their language and taxonomy for representing data privacy primitives.
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Privacy-as-Code: Preventing Facebook’s $5B violation using Fides Open-Source
Fides is built to solve for problems like this. In its current release, you can already draft a policy in YAML using fideslang and enforce that policy to ensure engineers across a team can’t accidentally or intentionally misuse data in a way that deviates from the promises a business or application makes to its users.
dvc
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My Favorite DevTools to Build AI/ML Applications!
Collaboration and version control are crucial in AI/ML development projects due to the iterative nature of model development and the need for reproducibility. GitHub is the leading platform for source code management, allowing teams to collaborate on code, track issues, and manage project milestones. DVC (Data Version Control) complements Git by handling large data files, data sets, and machine learning models that Git can't manage effectively, enabling version control for the data and model files used in AI projects.
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Why bad scientific code beats code following "best practices"
What you’re describing sounds like DVC (at a higher-ish—80%-solution level).
https://dvc.org/
See pachyderm too.
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First 15 Open Source Advent projects
10. DVC by Iterative | Github | tutorial
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Platforms such as MLflow monitor the development stages of machine learning models. In parallel, Data Version Control (DVC) brings version control system-like functions to the realm of data sets and models.
- ML Experiments Management with Git
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Git Version Controlled Datasets in S3
I was using DVC (https://dvc.org/) for some time to help solve this but it was getting hard to manage the storage connections and I would run into cache issues a lot, but this solves it using git-lfs itself.
- Ask HN: How do your ML teams version datasets and models?
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Exploring MLOps Tools and Frameworks: Enhancing Machine Learning Operations
DVC (Data Version Control):
- Evaluate and Track Your LLM Experiments: Introducing TruLens for LLMs
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[D] Is there a tool to keep track of my ML experiments?
I have been using DVC and MLflow since then DVC had only data tracking and MLflow only model tracking. I can say both are awesome now and maybe the only factor I would like to mention is that IMO, MLflow is a bit harder to learn while DVC is just a git practically.
What are some alternatives?
fiftyone - The open-source tool for building high-quality datasets and computer vision models
MLflow - Open source platform for the machine learning lifecycle
differential-privacy-library - Diffprivlib: The IBM Differential Privacy Library
lakeFS - lakeFS - Data version control for your data lake | Git for data
datahub - The Metadata Platform for your Data Stack
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]
awesome-machine-unlearning - Awesome Machine Unlearning (A Survey of Machine Unlearning)
delta - An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
pandas-datareader - Extract data from a wide range of Internet sources into a pandas DataFrame.
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
CKAN - CKAN is an open-source DMS (data management system) for powering data hubs and data portals. CKAN makes it easy to publish, share and use data. It powers catalog.data.gov, open.canada.ca/data, data.humdata.org among many other sites.
aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.