MLOps, short for Machine Learning Operations, is a set of practices that combines machine learning, DevOps, and data engineering. Its goal is to streamline the deployment, monitoring, and management of machine learning models in production. By integrating these disciplines, MLOps helps teams collaborate more effectively and ensures that models perform well over time. The MLOps process includes stages like data preparation, model training, and continuous integration and delivery. Tools and frameworks are often used to automate these processes, making it easier to update models and maintain their accuracy. This approach is essential for organizations looking to leverage artificial intelligence in a reliable and scalable manner.