tensorboardX
aim
| tensorboardX | aim | |
|---|---|---|
| 1 | 70 | |
| 7,801 | 4,816 | |
| - | 2.2% | |
| 7.0 | 8.0 | |
| 6 months ago | 1 day ago | |
| Python | Python | |
| MIT License | 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.
tensorboardX
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[D] 2022 State of Competitive ML -- The Downfall of TensorFlow
Tensorboardx is your friend: https://github.com/lanpa/tensorboardX
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?
ivy - The Unified Machine Learning Framework [Moved to: https://github.com/unifyai/ivy]
tensorboard - TensorFlow's Visualization Toolkit
oobabooga-macOS - Optimizing performance, building and installing packages required for oobabooga, AI and Data Science on Apple Silicon GPU. The goal is to optimize wherever possible, from the ground up.
dvc - 🦉 ML Experiments and Data Management with Git
tbparse - Load tensorboard event logs as pandas DataFrames for scientific plotting; Supports both PyTorch and TensorFlow
guildai - Experiment tracking, ML developer tools
tfgraphviz - A visualization tool to show a TensorFlow's graph like TensorBoard
wandb - 🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
datasets - 🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
ivy - The Unified AI Framework
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]