[Paper Reading] Deploy ML Models from Lab to Production

Session led by: Akshika Wijesundara PhD

If you don't have a Taro Premium membership, you can get it with a discount with Akshika's special link here: https://www.jointaro.com/r/akshikw802/

WHAT YOU'LL LEARN

• Discover the benefits of CI/CD pipelines: Learn how CI/CD pipelines streamline the model building, testing, and deployment processes, enabling rapid iteration and continuous improvement.
• Containerize your ML code: Understand the steps and advantages of containerizing your machine learning code to ensure consistency, portability, and efficient resource management.
• Leverage the AWS stack for ML workloads: Explore how to effectively utilize AWS as your cloud infrastructure provider to run and scale your machine learning workloads with ease and reliability.

WHY THIS TOPIC MATTERS

MLOps isn't just about fancy models - it's about getting them working for real! Learn how to deploy, maintain, and collaborate on ML projects, making you a highly-demand expert who can turn machine learning into real-world impact.