Machine Learning Operations (MLOps) is like DevOps for the machine learning lifecycle. This includes things like model deployment & management and data tracking, which help with productionizing machine learning models.
Through the survey below, we’d love to get feedback on your current DevOps practices as well as your prospective usage of MLOps in .NET. We’ll use your feedback to drive the direction of MLOps support in .NET.
The post MLOps: DevOps for Machine Learning appeared first on .NET Blog.
I remember deciding to pursue my first IT certification, the CompTIA A+. I had signed…
Key takeaways The transformer architecture has proved to be revolutionary in outperforming the classical RNN…
Once we learn how to deploy an Ubuntu server, how to manage users, and how…
Key-takeaways: Clean code isn’t just a nice thing to have or a luxury in software projects; it's a necessity. If we…
While developing a web application, or setting dynamic pages and meta tags we need to deal with…
Software architecture is one of the most discussed topics in the software industry today, and…