Ksenia Melnikova: Model Lifecycle Management System

Data Fest Online 2020 ML REPA Track With the development of AI technology in all industries, the problem of reproducibility became highly important: it sharply affects the timing and cost of the development. Reproducibility also impacts on quality and performance of the final AI model, which is supposed to be implemented into production. This problem appears because of a lack of development process organization, unstructured workflow, and sometimes even low information sharing. To find a solution, we will discuss the common Model Lifecycle by overviewing the AI development process step by step, define what is Model Lifecycle Management System and how it can help a data scientist to control the results and make a model reproducible.