To streamline the process of production, maintenance and monitoring of machine learning models, organizations deploy MLOps.
It allows for collaboration between data scientists, IT and developers for smooth communication.
The lifecycle of machine learning comes with complexity, such as data ingest, model deployment, training, monitoring and more, making its implementation complicated. There is also the need for collaboration between data scientists, data engineers, etc. This, in turn, requires rigorous operational synchronization between all touchpoints to work smoothly. This is why organizations have started utilizing MLOps.
MLOps, or Machine Learning Operations with serverless solutions, provide organizations with scalability, lower risk, efficiency, continuous improvement of their lifecycle and automated generation of predictions. This is why organizations deploy MLOps, and its integration is increasing.
The vast benefits provided by MLOps are getting banked on by various organizations in different industries. Here are a few examples:
Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.