From Experimentation to Implementation: Building a Successful MLops Framework for Scalable Machine Learning
Introduction to MLops Source: ml-ops.org Machine Learning Operations, also known as MLops, is a crucial aspect of the modern data-driven world. As machine learning models become more complex, and organizations strive to derive meaningful insights from vast amounts of data, the need for a streamlined and efficient MLops framework has become paramount. In this article, we will explore what MLops is, why it is important, and how it can be implemented to build a successful and scalable machine learning infrastructure. What is MLops and Why is it Important? Source: zenml.io MLops refers to the practices, processes, and tools used to streamline and automate the deployment, monitoring, and management of machine learning models in production environments. It combines the principles of software engineering, data engineering, and operations to ensure the smooth integration and operation of machine learning systems. The importance of MLops lies in its ability to bridge the gap between data scie...