08.29.2023
New Releases, Enhancements, Changes + Arize in the News!
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New Releases, Enhancements, Changes + Arize in the News!
Last updated
Was this helpful?
Customers who store their model data in Databricks can now send this data to Arize through a Databricks table import job. Learn how to set up an import job using Databricks .
Users can now create line charts with drift metrics. After selecting a model, select any drift metric corresponding to the model & dimension type (PSI, KL Divergence, Euclidean Distance, KS statistic). Users can select custom comparison baselines - pinpointing specific versions and/or batches and selecting a moving window from production.
Account Admins can now choose create users with temporary passwords. Upon logging in with a temporary password, users will be prompted to immediately change their password.
Admins can now also reset a user’s password on their behalf, either by sending a reset password link, or by issuing a temporary password.
The latest in educational and enablement content from Arize!
New modules covering key concepts and best practices for leveraging LLMs effectively in the real world.
The Table View enables users to see and interact with individual records in a simple table. This is similar to a df.head within a notebook environment. Explore any column in your data, including features and tags, using the Primary Column selector. Customize your table view by adding/removing columns, and re-ordering columns. Learn more .
The Embeddings Projector view automatically surfaces the worst performing clusters for quick troubleshooting. This additional view is especially helpful when troubleshooting LLMs with prompts and responses, where switching between the Table, Embeddings Projector, and Slice views can help teams get a full picture of how their LLM is performing. Learn more .
You can use any model available in the , public or private. If you are using a private model, you will need to with Hugging Face first. Learn more .
Catch up on the latest in with these new community readings:
with authors Xuefei Ning and Zinan Lin
with guest Frank Liu, Director of Operations, and ML Architect at Zilliz
🚧 + Guardrails AI: Safeguarding LLMs
🤖 : When and How To Implement LlamaIndex, BabyAGI, LangChain, and other tools
▶️ : Tips and Tricks
🤏 : Introduction and Best Practices
📡 : Code-Along Guide
📐 : When and Where To Use
📏 : Primer
We’re thrilled to announce that to supercharge the machine learning (ML) toolchain and streamline how our joint customers access, analyze, and act on their machine learning model insights.
and Arize’s new integration enables teams to rapidly deploy ML models into production with one line of code and begin monitoring and fine tuning instantly.
