Overview
MLOps, or Machine Learning Operations, is a set of practices that combines machine learning and DevOps. It helps teams manage the lifecycle of machine learning models, from development to deployment and monitoring. Understanding MLOps is essential for efficiently building and maintaining ML systems, ensuring they are reliable and scalable in real-world applications.
📚 Key Learning Objectives
- ✓ Define MLOps and its importance in machine learning.
- ✓ Identify the key components of the MLOps lifecycle.
- ✓ Explain the role of automation in MLOps.
- ✓ Describe best practices for deploying machine learning models.
- ✓ Assess the performance of ML models in production.
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