Databricks has helped automate machine learning pipelines by integrating the Data Lakehouse architecture with MLflow for scalable model lifecycle management. This unified platform enables seamless data-native ML workflows, simplifying data preparation, training, deployment, and monitoring. By automating repetitive tasks and providing end-to-end visibility, Databricks accelerates development cycles, ensures model reliability, and improves collaboration across teams, empowering organizations to efficiently scale their machine learning initiatives with greater accuracy and faster time-to-value.

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