In the ever-evolving landscape of technology and Generative AI, integrating DevOps principles into the machine learning (ML) lifecycle is a transformative game-changer. The challenges of deploying, utilizing, and monitoring ML models in production require specialized attention.

Join me for an insightful session where we will explore essential aspects such as mlflow, deployment patterns, and monitoring techniques for ML models. Gain a deeper understanding of how to effectively navigate the complexities of deploying ML models into production environments. Discover best practices and proven strategies for monitoring and observing ML models in real-world scenarios.

By attending this session, you will acquire valuable insights and practical knowledge to overcome the unique hurdles of scaling and bringing AI into production. Unlock the full potential of your ML models by embracing the powerful integration of DevOps principles. This presentation is based on the extensive customer research I conducted to write the Best Seller book - Scaling Machine Learning with Spark - https://www.amazon.com/Scaling-Machine-Learning-Spark-Distributed/dp/1098106822.