AI in Action: Deploying and Serving Production Quality AI Applications

With the increased focus on implementing AI and machine learning, the ability to effectively serve, govern, and track model APIs is crucial for maintaining both performance as well as compliance. This session delves into the best practices for managing the lifecycle of AI models in production environments, focusing on governance frameworks, monitoring strategies, and performance tracking methodologies. Participants will learn how to ensure their model APIs are not only high-performing and scalable but also adhere to evolving regulatory standards and organizational policies.

Through real-world examples and practical advice, we'll explore techniques for optimizing model delivery, enhancing transparency, and ensuring accountability in model operations. Whether you're a data scientist, ML engineer, or AI governance professional, this session will equip you with the knowledge to build robust systems for serving and overseeing your AI models, enabling you to unlock their full potential while mitigating risks and ensuring compliance.