Logging — The Effective Management of Machine Learning Systems

Understanding, Elements, Levels, and Guided Walkthrough of Logging in MLOps

Table of Contents:

1. Why Logging?
2. Key Logging Components
3. Hierarchies of Logging Implementation
4. A step-by-step guide to implementing efficient logging for Machine Learning in Python

Efficiency and reliability are critical in the dynamic field of machine learning (ML). Amidst these priorities, logging often goes unnoticed. However, the logging plays an important role: it not only monitors the state of the machine learning system, but also helps in debugging, tuning model performance, and ensuring transparency. This article explores the importance of the logging, breaks down its essential components, explores different levels of implementation, and walks you through setting up a powerful Python-based logging, all in the context of machine learning systems.

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Photo by Luca Bravo on Unsplash

1. Why Logging?

Logging, in the context of a machine learning system, involves recording pertinent details about model execution, data…