Recently, there has been a lot of talk about MLOps from the DevOps and software engineering perspective. The message often comes across as, “Hurry, DevOps community, let’s set some standards before MLOps reinvents the wheel,” or “The purpose of MLOps is to allow anyone who knows how to code to get ML into production.” Let […]
Building Your Data Science Team from Within
The global machine learning (ML) industry is increasing at a compound annual growth rate of 42% and will be worth $9 billion toward the end of 2022. Despite this figure, there are many cases of data science teams’ failure to deploy a reliable artificial intelligence (AI) product or service. Part of the failings and shortcomings of AI […]