👉 Tagged engineering is an advanced software development methodology that integrates the principles of software engineering with machine learning and data science, specifically focusing on the creation of models that are interpretable, explainable, and maintainable. Unlike traditional machine learning approaches where the focus is primarily on model accuracy, tagged engineering emphasizes the importance of understanding how and why a model makes its predictions. This is achieved by tagging each input feature with metadata that describes its relevance, importance, and potential impact on the model's output. This tagging process allows developers to trace back predictions to specific features, enhancing transparency and trust in the model's decisions. Additionally, tagged engineering facilitates better collaboration between data scientists and domain experts by providing clear, structured insights into the model's behavior, making it easier to debug, optimize, and deploy in real-world applications.
