tensorboard
aim
Our great sponsors
| tensorboard | aim | |
|---|---|---|
| 11 | 70 | |
| 6,539 | 4,782 | |
| 0.9% | 3.1% | |
| 9.4 | 8.0 | |
| 6 days ago | 3 days ago | |
| TypeScript | 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.
tensorboard
- Tensorboard
-
[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
-
[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
-
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.
-
[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
-
📖 👆🏻 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.
aim
-
aim VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
-
End-to-end observability for LlamaIndex environment
LlamaIndex Observer is one of the logging apps built in AimOS (aimstack.io).
-
Data Registry suggestions for ML projects
I've been working with Aim for a while, and it's been solid. What stands out for me is its open-source nature. https://aimstack.io/
-
Building and debugging LLMs with Aim: self-hosted and open-source AI metadata tracking tool
If you haven't yet, drop a star to support open-source project! ⭐️ https://github.com/aimhubio/aim
-
Any tools that offer In-depth tracking of model runtime performance?
Here is the GitHub repository: https://github.com/aimhubio/aim
-
Using MLflow(Machine Learning experimentation tracking tool) in Kaggle notebooks with the help of DagsHub
You can also check out Aim, which has an integration with MLflow, called aimlflow.
-
Visualize metadata with Aim on Hugging Face Spaces and seamlessly share training results with anyone
Hope you enjoyed reading and thanks for your time! Feel free to share your thoughts, would love to read them. Support Aim by dropping a star on GitHub: https://github.com/aimhubio/aim
-
Effortless image tracking and analysis for 3D segmentation task with Aim
Aim: An easy-to-use & supercharged open-source AI metadata tracker aimstack.io
-
Evaluate Different Vector Databases
Seems useful: https://github.com/aimhubio/aim
- Metadata visualization via Aim Explorers
What are some alternatives?
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.
guildai - Experiment tracking, ML developer tools
tesseract-ocr - Tesseract Open Source OCR Engine (main repository)
models - Models and examples built with TensorFlow
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
rustboard - just-for-fun reimplementation of TensorBoard backend in Rust
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]
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!