What is Lineage Tracking in Machine Learning and why you need It

Lineage Tracking is an essential feature for managing machine learning (ML) pipelines, ensuring that all assets consumed and produced during ML tasks are systematically tracked, thereby maintaining a reliable source of truth. This process is crucial for bookkeeping, debugging, traceability, compliance, and reproducibility, as it allows ML engineers to trace back all input parameters and configurations that lead to a particular model's outcome. Instead of manually logging data in spreadsheets or notebooks, which is cumbersome and inefficient, Lineage Tracking should be integrated into the ML platform itself. Sematic, an open-source Continuous Machine Learning platform, simplifies this by allowing users to define end-to-end ML pipelines in Python without requiring infrastructure skills, while inherently providing comprehensive traceability and lineage tracking. Sematic tracks various components such as code, configurations, input data, and resources, ensuring that the reproducibility of ML pipelines is easily achievable.