April 30, 2024Machine Learning Engineering and Operations
Author: Segun Adelowo Based on my experience here is a summary for individuals interested in getting started in Machine Learning Engineering and Machine Learning Operations and who want to improve their skills. Content: Model production challenges (O Model, where is thy value?) What is Machine Learning Engineering? Machine Learning Production Steps Career Growth for a Machine Learning Engineer Resources What is Machine Learning Operations? Machine Learning Operations Steps Career Growth for a Machine Learning Operations Engineer Roles and Skills for MLE and MLOPs Additional Resources O Model, where is thy value? ML and MLOPs are still in their early years, there is no universal standard for doing ML and MLOPS yet when compared to software engineering. A few of the most common reasons why ML models don’t get to production or thrive in production include: One major issue is that POCs are typically built with a limited scope and a specific set of data, which may not be representative of the real-world conditions in which the model will be deployed.
