Data is continuing to prove to be a valuable asset for businesses of all sizes. I say that both from the fact that consulting firms like McKinsey have found that in their research companies that are using AI and analytics can attribute 20% of their earnings to it. Similarly, I have been able to consult for […]
Photo by Karo Kujanpaa on Unsplash By Travis Wolf Introduction — “What is MLOps? — DevOps for ML” — Kaz Sato Challenges arise as the production of machine learning models scale up to an enterprise level. MLOps plays a role in mitigating some of the challenges like handling scalability, automation, reducing dependencies, and streamlining decision making. Simply […]
Background In 2014 a group of Google researchers put out a paper titled Machine Learning: The High-Interest Credit Card of Technical Debt. This paper pointed out a growing problem that many companies might have been ignoring. Using the framework of technical debt, we note that it is remarkably easy to incur massive ongoing maintenance costs at the […]
Photo by Markus Spiske on Unsplash Python really is everywhere at this point. Although many gatekeepers argue whether a person is really a software developer if they don’t code in a language more difficult than Python, it still is everywhere. It’s used to automate, manage websites, analyze data, and wrangle big data. As data grows, the way we manage it […]