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An easy-to-use & supercharged open-source experiment tracker

Aim logs your training runs and any AI Metadata, enables a beautiful UI to compare, observe them and an API to query them programmatically.

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_{SEAMLESSLY INTEGRATES WITH:}

_{TRUSTED BY ML TEAMS FROM:}

AimStack offers enterprise support that's beyond core Aim. Contact via hello@aimstack.io e-mail.

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About • Demos • Ecosystem • Quick Start • Examples • Documentation • Community • Blog

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ℹ️ About

Aim is an open-source, self-hosted ML experiment tracking tool designed to handle 10,000s of training runs.

Aim provides a performant and beautiful UI for exploring and comparing training runs. Additionally, its SDK enables programmatic access to tracked metadata — perfect for automations and Jupyter Notebook analysis.

Aim's mission is to democratize AI dev tools 🎯

🎬 Demos

Check out live Aim demos NOW to see it in action.

| Machine translation experiments | lightweight-GAN experiments| |:---:|:---:| | | | | Training logs of a neural translation model(from WMT'19 competition). | Training logs of 'lightweight' GAN, proposed in ICLR 2021. |

| FastSpeech 2 experiments| Simple MNIST | |:---:|:---:| | | | | Training logs of Microsoft's "FastSpeech 2: Fast and High-Quality End-to-End Text to Speech". | Simple MNIST training logs. |

🌍 Ecosystem

Aim is not just an experiment tracker. It's a groundwork for an ecosystem. Check out the two most famous Aim-based tools.

| aimlflow | Aim-spaCy | |:---:|:---:| | | | | Exploring MLflow experiments with a powerful UI | an Aim-based spaCy experiment tracker |

🏁 Quick start

Follow the steps below to get started with Aim.

1. Install Aim on your training environment

pip3 install aim

2. Integrate Aim with your code

from aim import Run
Initialize a new run
run = Run()
Log run parameters
run["hparams"] = {
    "learning_rate": 0.001,
    "batch_size": 32,
}
Log metrics
for i in range(10):
    run.track(i, name='loss', step=i, context={ "subset":"train" })
    run.track(i, name='acc', step=i, context={ "subset":"train" })

_See the full list of supported trackable objects(e.g. images, text, etc) here._

3. Run the training as usual and start Aim UI

aim up

Learn more