The most advanced ML Observability platform
We’re super excited to share that Aporia is now the first ML observability offering integration to the Databricks Lakehouse Platform. This partnership means that you can now effortlessly automate your data pipelines, monitor, visualize, and explain your ML models in production. Aporia and Databricks: A Match Made in Data Heaven One key benefit of this […]
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We’re excited 😁 to share that Forbes has named Aporia a Next Billion-Dollar Company. This recognition comes on the heels of our recent $25 million Series A funding and is a huge testament that Aporia’s mission and the need for trust in AI are more relevant than ever. We are very proud to be listed […]
Features don’t appear out of thin air – they are usually constructed using various transformations on raw data, that was either part of a data-set or received at runtime from a user.
We refer to that raw data as the raw_inputs of a model.
For example, your dataset might contain a column with state names – you will then have some preprocessing code convert that raw_input to a feature using one-hot encoding.
