Machine Learning in Practice - How to Build and Deploy ML Projects

摘要

Machine Learning projects have already shown significant value in variety of areas, including design and validation fields. However, in practice, the process of bringing a valuable ML project into production can come across many hurdles, thus It is extremely difficult to truly embed them in the core processes of the organization. In this tutorial we will present some best practices in working on ML projects, deploying them in core processes, and maximizing the value they create. We will focus on CRISP-DM methodology, Agile ML development process and others topics, as well as present some examples from projects conducted for Intels validation teams.