How to enable the Practice of MLOps for Continuous Integration and Development of the Machine Learning Models.
How Seeq enables the Practice of MLOps for Continuous Integration and Development of the Machine Learning Models
Using ML/AI now they have enabled themselves to not only understand the importance of parameters but also to make predictions in real-time and forecast the future values. This helps the industry to manage and continuously improve the process by mitigating operational challenges such as reducing downtime, increasing productivity, improving yields and much more. But, in order to achieve such continuous support for the operations in real-time, the underlying models and techniques also need to be continuously monitored and managed. This brings in the requirement of MLOps, a borrowed terminology from DEVOps that can be used to manage your model in a receptive fashion using its CI/CD capabilities. Essentially MLOps enables you to not only develop your model but also gives you the flexibility to deploy and manage them in the production environment.