Explore the lifecycle of deep learning models at Uber in this 44-minute conference talk by Jai Ranganathan, former VP of AI and Data at Uber. Gain insights into customer-centric approaches, ticket complexity analysis, and model exploration processes. Learn about data modeling types, cost-benefit tradeoffs, and final architecture considerations. Discover techniques for model validation, open-source visualization, and entity recognition. Delve into challenges such as distributed training with Spark, testing strategies, and performance metrics. Understand the importance of monitoring, retraining pipelines, and managing training data in a large-scale AI environment.