While machine learning projects and traditional software development have many similarities, there are some important differences. This means blindly applying the practices of one to the other is unlikely to be successful. »
There are many lessons and good practices we've learned from decades of software development and more than a decade of "DevOps". Most (but not all) of these can be applied to machine learning projects. »
MLOps and AIOps both sit at the union of DevOps and AI. They may sound like the same thing, but they represent completely different ideas. So what is AIOps? »
MLOps sounds like just another buzzword, but it presents some important concepts and practices for maturing your machine learning projects. »
The terms "Artificial Intelligence" and "Machine Learning" are often used synonymously, but they don't mean the same thing. So what's the difference? »