In this quest, you will dive deep into the advanced techniques of deploying machine learning models in real-world scenarios. You'll begin by understanding the principles of model serving, including RESTful APIs and gRPC, and explore various deployment options such as cloud services, Docker containers, and Kubernetes orchestration. The quest will guide you through the entire lifecycle of deployment—from model training to monitoring performance in production. You will learn about version control for models, A/B testing strategies, and how to ensure reproducibility and scalability. By the end of this quest, you will have hands-on experience with deploying a model and managing its lifecycle, equipping you with the skills needed to handle real-world machine learning projects effectively.
