An independent survey has uncovered yet another hurdle to delivering value with AI. Challenges related to people, process, and tools are creating friction that makes it difficult to track model training runs and results, collaborate with colleagues, and iterate faster during the complex process of developing machine learning. This friction can cause delays in ML development that delay or halt model deployment to production.
But there’s good news: In this webinar, Comet CEO and co-founder Gideon Mendels will review the results of Comet’s 2021 ML Practitioner Survey and share insights for overcoming ML development challenges. You will learn about:
- Key challenges faced by ML practitioners
- Helpful tools and approaches for building and deploying ML at scale
- Three characteristics to consider when evaluating a machine learning platform