AI Engineering Management: Is There a Methodology for AI Model Development?
Link for non-members: https://mrmanna.medium.com/ai-engineering-management-is-there-a-methodology-for-ai-model-development-63db40968461?sk=382451c9e36238c0b229c1d6c0fc1eab
In the realm of AI product development, methodology is not just a theoretical concept but a guiding framework that ensures teams can navigate the complexities of creating data-driven products. Two popular methodologies, OSEMN and CRISP-DM, are often referenced when discussing data science workflows. But what distinguishes them? And how do they translate into practical, real-world AI product development? Let’s break them down.
What is OSEMN? (Awesome Methodology)
OSEMN is an acronym for Obtain, Scrub, Explore, Model, and Nnterpret. The methodology has earned the playful pronunciation of “Awesome,” reflecting its structured yet flexible approach that is ideal for data-centric product development. Here’s a quick overview of each phase:
- Obtain: This is the first step, where the primary focus is on gathering data from various sources. It can include data scraping, APIs, sensors…
