Building a machine learning (ML) model is just the beginning of the journey. The real challenge lies in taking that model to production, maintaining it over time and ensuring it continues to perform reliably in real-world scenarios. This is where MLOps comes into play. To help beginners and practitioners navigate this complex process, the open-source MLOps-Basics repository by Raviraja Ganta offers a structured, hands-on approach to learning end-to-end ML operations.
In this blog, we will talk about the fundamentals of MLOps, explore key tools like Hydra for configuration management and DVC for data version control, and show how projects like MLOps-Basics simplify learning these concepts for beginners.
Image Source : MLOps-Basics Github Repo
What is MLOps-Basics?
MLOps-Basics is a GitHub repository designed to teach the fundamentals of MLOps through a simple classification problem. Instead of overwhelming learners with abstract concepts, it provides a step-by-step, week-by-week learning path that covers everything from data processing and model training to deployment and prediction monitoring.
By the end of the journey, users will not only understand how to build ML models but also how to scale…
