In this webinar, we will cover some of the latest innovations brought into the Databricks Unified Analytics Platform for Machine Learning, including:
Get started quickly using the Databricks Runtime 5.0 for Machine Learning, that provides a pre-configured Databricks clusters including the most popular ML frameworks and libraries, Conda support, performance optimizations, and more.
Track, tune, and manage models, from experimentation to production, with MLflow, an open-source framework for the end-to-end Machine Learning lifecycle that allows data scientists to track experiments, share and reuse projects, and deploy models quickly, locally or in the cloud.
Scale up deep learning training workloads from a single machine to large clusters for the most demanding applications using the new HorovodRunner.