You’ve taken your first steps into the exciting world of machine learning, and now you’re ready to bring your models to life in a production environment on AWS. Join this session, “Machine Learning 102: Deploying to AWS Production,” designed for developers who have dipped their toes into machine learning and are eager to learn the ropes of deploying models in a real-world setting. Whether you’re a Python-savvy coder or just starting to explore the possibilities of machine learning, this presentation will guide you through the essential steps of transitioning from model creation to deployment.

In this interactive session, we’ll delve into the intricacies of deploying machine learning models on AWS. Learn what to do, what to avoid, and uncover some nifty tricks along the way. Through live demonstrations, we’ll walk through the process of setting up your machine learning model in a production environment, addressing common challenges and showcasing best practices. From handling your own data to making use of existing models, we’ve got you covered. Whether you’re interested in deploying your first model or refining your deployment skills, this session is tailored to equip you with the practical knowledge you need.

Moreover, we’ll explore the world of MLOps - the intersection of machine learning and operations. Discover how MLOps practices streamline the deployment lifecycle, ensuring scalability, reliability, and maintainability of your machine learning applications. Gain insights into integrating your workflows seamlessly into AWS, and leave with a solid understanding of the essential concepts that bridge the gap between development and operations in the machine learning space. Don’t miss this opportunity to level up your skills and unlock the full potential of deploying machine learning models in an AWS production environment. Join us for an engaging session that empowers you to take your machine learning projects to the next level!