Taking Deep Learning to Production with MLflow and RedisAI

Explore the integration of MLflow and RedisAI for efficient deep learning model deployment in this 30-minute talk from Databricks. Learn how to leverage Redis modules and C APIs to create a reliable runtime for deep learning workloads, transforming Redis into a model serving microservice. Discover RedisAI's key features, including multi-framework support, CPU and GPU backend, auto batching, and DAGing. Follow along as the speaker demonstrates how to build a streamlined productionization pipeline, addressing the challenges of taking deep learning models to production reliably. Gain insights into production strategies, requirements, and the practical implementation of RedisAI in your MLOps workflow.