Machine Learning Operations (MLOps) is based on DevOps principles and practices—including continuous integration, delivery and deployment—that increase the efficiency of workflows. MLOps applies these principles to the Machine Learning process, with the goal of:
● Faster experimentation and development of models
● Faster deployment of models into production
● Quality assurance and end-to-end lineage tracking
In this White Paper, you will be introduced to the different everyday life challenges of a Data scientist during the lifecycle of a model and their real world solution and area of improvment!
