tbparse
aim
| tbparse | aim | |
|---|---|---|
| 1 | 70 | |
| 158 | 4,797 | |
| - | 1.8% | |
| 5.9 | 8.0 | |
| 5 months ago | 2 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.
tbparse
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[P] tbparse: Load tensorboard event logs as pandas DataFrames for scientific plotting; Supports both PyTorch and TensorFlow
The package is open source (https://github.com/j3soon/tbparse) and the usages are documented in detail (https://tbparse.readthedocs.io/en/latest/). My friends and I have been using it for a while and find it very convenient, so I think some of you may benefit from it. I would be happy to hear your feedback and feature requests.
aim
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aim VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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End-to-end observability for LlamaIndex environment
LlamaIndex Observer is one of the logging apps built in AimOS (aimstack.io).
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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/
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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
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Any tools that offer In-depth tracking of model runtime performance?
Here is the GitHub repository: https://github.com/aimhubio/aim
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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.
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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
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Effortless image tracking and analysis for 3D segmentation task with Aim
Aim: An easy-to-use & supercharged open-source AI metadata tracker aimstack.io
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Evaluate Different Vector Databases
Seems useful: https://github.com/aimhubio/aim
- Metadata visualization via Aim Explorers
What are some alternatives?
tensorboardX - tensorboard for pytorch (and chainer, mxnet, numpy, ...)
tensorboard - TensorFlow's Visualization Toolkit
oneline - Read a text file, one line at a time
dvc - 🦉 ML Experiments and Data Management with Git
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
guildai - Experiment tracking, ML developer tools
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
wandb - 🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
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]
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
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!