Streamline MLOps With MLflow Model Registry Webhooks
As machine learning becomes more widely adopted, businesses need to deploy models at speed and scale to achieve maximum value. Today, we are…
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 v0.9.0 Features SQL Backend, Projects in Docker, and Customization in Python Models
MLflow v0.9.0 was released today. It introduces a set of new features and community contributions, including SQL store for tracking server, support for…
Build, Scale, and Deploy Deep Learning Pipelines with Ease
At the Spark Summit in San Francisco in June, we announced an open-source project Deep Learning Pipelines. Deep Learning Pipelines provides high-level APIs…
A Vision for Making Deep Learning Simple
When MapReduce was introduced 15 years ago, it showed the world a glimpse into the future. For the first time, engineers at Silicon…
Intel’s BigDL on Databricks
Intel recently released its BigDL project for distributed deep learning on Apache Spark. BigDL has native Spark integration, allowing it to leverage Spark…
