Announcing the General Availability of Databricks Feature Serving
Today, we are excited to announce the general availability of Feature Serving. Features play a pivotal role in AI Applications, typically requiring considerable...
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Improve your RAG application response quality with real-time structured data
Retrieval Augmented Generation (RAG) is an efficient mechanism to provide relevant data as context in Gen AI applications. Most RAG applications typically use...
How Lakehouse AI improves model accuracy with real-time computations
The predictive quality of a machine learning model is a direct reflection of the quality of data used to train and serve the...
The Simplification of AI Data
Talk to any data science organization and they will almost unanimously tell you that the biggest challenge to building high quality AI models...
Best Practices for Realtime Feature Computation on Databricks
As Machine Learning usage continues to rise across industries and applications, the sophistication of the Machine Learning pipelines is also increasing. Many of...
Announcing General Availability of Databricks Feature Store
Today, we are thrilled to announce that Databricks Feature Store is generally available (GA)! In this blog post, we explore how Databricks Feature...
Databricks Announces the First Feature Store Co-designed with a Data and MLOps Platform
Today, we announced the launch of the Databricks Feature Store , the first of its kind that has been co-designed with Delta Lake...
MLflow Model Registry on Databricks Simplifies MLOps With CI/CD Features
MLflow helps organizations manage the ML lifecycle through the ability to track experiment metrics, parameters, and artifacts, as well as deploy models to...
Databricks Extends MLflow Model Registry with Enterprise Features
We are excited to announce new enterprise grade features for the MLflow Model Registry on Databricks. The Model Registry is now enabled by...
MLflow 0.2 Released
At this year’s Spark+AI Summit , we introduced MLflow , an open source platform to simplify the machine learning lifecycle. In the 3...