MLOps Fundamentals (GK840034)

MLOps Fundamentals is a comprehensive guide to the principles, components, and tools used in Machine Learning Operations (MLOps). It provides a thorough understanding of the machine learning lifecycle, MLOps lifecycle, and the benefits and tools involved, such as MLFlow and KubeFlow.We will take a look at setting up an ML project, including using Git and GitHub, setting up virtual environments, and pre-commit hooks. The course will then delve into the fundamentals of data management, such as understanding data lifecycles, data versioning, governance, and storage solutions.Practical, hands-on demonstrations will be provided on Exploratory Data Analysis (EDA), feature engineering, and data cleaning using pandas and matplotlib. The course will further explore the concept of feature stores, their types, working, best practices, and implementation challenges.