En camino a MLOPS: Cómo definir el framework adecuado para tus operaciones de aprendizaje automático

Delve into the realm of MLOps, targeting newcomers and emphasizing strategies applicable to both startups and established organizations. Jorge sheds light on the process of crafting an optimal MLOps framework, considering factors such as cost, flexibility, and community engagement. Jorge addresses the complexities of switching between frameworks, analyzing the pros and cons of open source versus enterprise solutions. He advocates for a collaborative approach, advocating the involvement of data scientists, engineers, and machine learning specialists to effectively navigate the challenges of implementing MLOps.