MLOps at Medium Scale
As machine learning becomes more prevalent, so does the need for MLOps.
MLOps, or DevOps for machine learning, is a set of practices that combine the development and operational aspects of machine learning.
The goal of MLOps is to help organizations improve the speed, quality, and efficiency of their machine learning development process.
MLOps includes practices such as automated machine learning (ML), continuous integration and delivery (CI/CD), and model management.
MLOps can help organizations to:
- Automate the process of training and deploying machine learning models
- Improve the quality and accuracy of machine learning models
- Reduce the time to deploy machine learning models
- Improve the efficiency of the machine learning development process
Why is MLOps important?
Machine learning is a powerful tool that can be used to automate various tasks. However, it is also important to ensure that the machine learning models are operated in a way that is both efficient and effective. This is where MLOps comes in.
MLOps is a set of practices that aim to improve the efficiency and effectiveness of…
