Informed Guesser, Minimum Viable Model, Heuristic First: Using ML to solve the Right Problems

In this webinar with Eduardo Bonet, Staff Full Stack Engineer – MLOps at Gitlab, we see as Machine Learning passes its hype, the industry now enters a more mature scene where ML is not perceived anymore as a magical wand, but as a risky, yet powerful, tool to solve a new set of problems, that requires heavy investments in people and infrastructure.

In this product-focused talk, we will be looking at steps we can take to decrease the risk of Machine Learning solution dying on the prototype phase: what types of problems are best fit, ideas on how to handle stakeholder expectations, how to translate Business Metrics into Model Metrics, and how to be more confident if we are solving the right problems.