For most businesses, machine learning seems close to rocket science, appearing expensive and talent demanding. And, if you’re aiming at building another Netflix recommendation system, it really is. But the trend of making everything-as-a-service has affected this sophisticated sphere, too. You can jump-start an ML initiative without much investment, which would be the right move if you are new to data science and just want to grab the low hanging fruit.
One of ML's…Continue
Added by Olexander Kolisnykov on September 18, 2018 at 2:52am — No Comments
Summary: Deep changes are underway in how data science is practiced and successfully deployed to solve business problems and create strategic advantage. These same changes point to major changes in how data scientists will do their work. Here’s why and how.
The outsourcing model which led to the “on-demand” “as a service” model, has taken off with increasing adoption of cloud-computing and mobility. What started out with the SaaS – software as a service model, has now diversified into several other services.
Indeed, cloud computing has come to rest on three of these as its core pillars: