In this webinar, we will cover some of the latest innovations brought into the Databricks Unified Analytics Platform for Machine Learning. In particular we will show you how to:
- 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.