telemetry-python
dvc
| telemetry-python | dvc | |
|---|---|---|
| 1 | 110 | |
| 3 | 13,189 | |
| - | 1.2% | |
| 2.6 | 9.6 | |
| 8 months ago | 6 days 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.
telemetry-python
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Data Version Control
VS Code, etc
> I think the challenge I have is that since you’re getting IP address that will be an opportunity to abuse.
Yes! And we are migrating to the new package / infrastructure because of this - https://github.com/iterative/telemetry-python (DVC's sister tool MLEM is already on it and it's not sending (saving) IP addresses, nor using GA or any other third-party tools, data is saved into BigQuery and eventually we'll make publicly accessible - https://mlem.ai/doc/user-guide/analytics to be fully GDPR compatible). It's a legacy system that DVC had in place. There was no intention to use those IP addresses in some way.
> I think perhaps the only other way would be to support an automated distro that doesn’t include it so users are at least able to easily choose a version.
Thanks. To some extent brew-like policy (not sending anything significant before there is a chance to disable it and there is clear explicit message) should be mitigating this, but I'll check if it works this way now and if it can be improved.
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?
Estranged.Lfs - A Git LFS server implementation in C# designed to run in a serverless environment.
MLflow - Open source platform for the machine learning lifecycle
Mimic - We use the actual live data from the International Space Station to control a 3D-printed model that moves the solar arrays and radiators to track the real ISS in real time. We also host two pages that display ALL of the public ISS telemetry below::
lakeFS - lakeFS - Data version control for your data lake | Git for data
dud - A lightweight CLI tool for versioning data alongside source code and building data pipelines.
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]
rudolfs - A high-performance, caching Git LFS server with an AWS S3 and local storage back-end.
delta - An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
git-submodules - Git Submodule alternative with equivalent features, but easier to use and maintain.
palm-dbt - dbt plugin for Palm CLI