guildai
Experiment tracking, ML developer tools (by guildai)
tensorboard
TensorFlow's Visualization Toolkit (by tensorflow)
Our great sponsors
| guildai | tensorboard | |
|---|---|---|
| 16 | 11 | |
| 856 | 6,539 | |
| 0.6% | 0.9% | |
| 8.8 | 9.4 | |
| 8 months ago | 3 days ago | |
| Python | TypeScript | |
| Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
guildai
Posts with mentions or reviews of guildai.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-05.
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guildai VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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[D] Who here are convinced that they have a really good setup that keeps track of their ML experiments?
Experiment tracking in DvC is implemented using git to store snapshots of a project and related artifacts. You might take a look at Guild AI's support for DvC, which is tightly integrated with DvC stages. You can run any of the stages defined for a project and you get a properly isolated run (each run is a project copy to ensure that you're not corrupting the run if you modify files while it's running - as well as properly supporting concurrent runs). Once you have runs in Guild, you can use any number of tools to study, compare, export, etc.
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[D] Deploying SOTA models into my own projects
I built an experiment tracking tool (Guild AI) that focuses on code/model reuse and so this question is dear to my heart :) Best of luck!
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[P] I reviewed 50+ open-source MLOps tools. Here’s the result
I'm not aware of experiment tracking in Jupyter notebooks themselves. Guild AI is able to run notebooks as experiments however.
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[D] What MLOps platform do you use, and how helpful are they?
Disclosure - I'm the author of Guild AI so take this for the biased opinion that it is.
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[N] Experiment tracking with DvC and Guild AI
I'm the author of Guild AI (open source experiment tracking). For some time now Guild users have asked for DvC support. This is now available as a pre-release.
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[D] Why doesn’t your team use an experiment tracking tool?
Guild AI now has support for running DvC stages as experiments. DvC uses git under the covers to manage project state for each experiment, along with the experiment results. Guild doesn't touch your git repo and instead copies your project source to a new run directory. This ensures that you have a correct record of your experiment without churning your project state.
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Data Science toolset summary from 2021
Guild.ai - https://guild.ai/
- [D] How do you ensure reproducibility?
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[D] I'm new and scrappy. What tips do you have for better logging and documentation when training or hyperparameter training?
Use guild and pytorch-lightning. Make it easy for new contributors to get your data by using dvc as a data access tool.
tensorboard
Posts with mentions or reviews of tensorboard.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-04-27.
- Tensorboard
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[D] Visualizing layer weights
Some form of 3D histograms? And then "discretized"/binned for each layer too. Apparently Tensorboard has them: https://github.com/tensorflow/tensorboard/blob/master/docs/r1/histograms.md
- I think I broke PIP
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[D] Unpopular Opinion: I hate the tensorboard Smoothing algorithm and always set the slider to 0.
Consider filing an issue? https://github.com/tensorflow/tensorboard/issues
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Parts of Tensorboard are being rewritten in Rust for a 100× to 400× speedup
The async code is in our server.rs and cli.rs, because this exposes a Tonic server and Tonic is all-in on async.
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[D] Comparison of experiment tracking tools
A quick google search is telling me that this is possible but very poorly documented / communicated: https://github.com/tensorflow/tensorboard/issues/767
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📖 👆🏻 Making the Printed Links Clickable Using TensorFlow 2 Object Detection API
The cool part about TensorBoard is that we may run it directly in Google Colab. However, if you're running the notebook in your local installation of Jupyter you may also install it as Python package and launch it from the terminal.
What are some alternatives?
When comparing guildai and tensorboard you can also consider the following projects:
MLflow - Open source platform for the machine learning lifecycle
aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
wandb - 🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
dvc - 🦉 ML Experiments and Data Management with Git
labelImg - LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
tesseract-ocr - Tesseract Open Source OCR Engine (main repository)
labml - 🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
models - Models and examples built with TensorFlow
rustboard - just-for-fun reimplementation of TensorBoard backend in Rust