ML Observability in your notebook
Project description
Phoenix provides MLOps insights at lightning speed with zero-config observability for model drift, performance, and data quality.
Phoenix is under active development. APIs may change at any time.
Installation
pip install arize-phoenix
Getting Started
In this section, you will get Phoenix up and running with a few lines of code.
After installing arize-phoenix
in your Jupyter or Colab environment, open your notebook and run
import phoenix as px
train_ds, prod_ds = px.load_dataset("sentiment_classification_language_drift")
px.launch_app(train_ds, prod_ds)
Next, visualize your embeddings and inspect problematic clusters of your production data.
TODO(#297): Include GIF where we navigate to embeddings, zoom in and rotate, and select a cluster.
Don't forget to close the app when you're done.
px.close_app()
For more details, check out the Sentiment Classification Tutorial.
Documentation
For in-depth examples and explanations, read the docs.
Community
Join our community to connect with thousands of machine learning practitioners and ML observability enthusiasts.
- 🌍 Join our Slack community.
- 💡 Ask questions and provide feedback in the #phoenix-support channel.
- 🌟 Leave a star on our GitHub.
- 🐞 Report bugs with GitHub Issues.
- 🗺️ Check out our roadmap to see where we're heading next.
- 🎓 Learn the fundamentals of ML observability with our introductory and advanced courses.
- ✏️ Check out our blog. TODO(#291): Add blog filter for Phoenix
- ✉️ Subscribe to our mailing list. TODO(#294): Add link
- 🐦 Follow us on Twitter.
- 👔 Check out our LinkedIn. TODO(#292): Add link, fix badge
Contributing
- 💻 Read our developer's guide.
- 🗣️ Join our Slack community and chat with us in the #phoenix-devs channel.
License
Arize-Phoenix is licensed under the Elastic License 2.0 (ELv2).
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for arize_phoenix-0.0.2rc3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b6dea022fd579346563579ef183745194301bf22e989562f33e7d0c920052c48 |
|
MD5 | f66f8a4d71bbab618237b27b9d0b06bf |
|
BLAKE2b-256 | 94e29f70c1bb0929ce8c68f3639d9b8fe8130d496ae70521e2afaf47c214a7b7 |