Data-driven products: from zero to hero

Karolina Griciunė

Machine learning (ML) models rarely make it to production. Often these projects start with intention ‘let’s make something cool’, but they get stuck in local Jupyter notebooks or Power Point presentations. What does it take to complete a data-driven product? I will talk about the importance of the problem and it's context definition, will give examples of overcomplication and together we will go through the steps required to build a data-driven product.