Introducing Databricks Machine Learning: a Data-native, Collaborative, Full ML Lifecycle Solution

Today, we announced the launch of Databricks Machine Learning, the first enterprise ML solution that is data-native, collaborative, and supports the full ML lifecycle. This launch introduces a new purpose-built product surface in Databricks specifically for Machine Learning (ML) that brings together existing capabilities, such as managed MLflow, and introduces new components, such as AutoML and the Feature Store. Databricks ML provides a solution for the full ML lifecycle by supporting any data type at any scale, enabling users to train ML models with the ML framework of their choice and managing the model deployment lifecycle – from large-scale batch scoring to low latency online serving. Many ML platforms fall short because they ignore a key challenge in ML: they assume that high-quality data is ready and available for training. That requires data teams to stitch together solutions that are good at data but not AI, with others that are good at AI but not data.