Enterprise organizations in every industry are adopting modern, advanced analytical techniques using AI and Machine Learning (ML) for a variety of different use cases.

However, many of these enterprises are struggling to operationalize these AI / ML environments for large-scale deployments across their data science and analyst teams. That's because they often implement anti-patterns or 'worst practices' that ultimately trip up those deployments. In this session, we'll explore the most common anti-patterns and how to avoid them ' while designing a strategy of best practices for AI / ML in the enterprise.