Data Challenges Unveiled
Demetrios shares his struggles with data as a critical bottleneck in the ML workflow, emphasizing its impact on model performance. Satish highlights the importance of understanding how data is sourced and transformed, pointing out the issue of "islands on the lake," where vast amounts of data exist but are not necessarily useful for training. Their discussion sheds light on the complexities of managing data in real business environments.In this clip
From this podcast
MLOps.community
Machine in Production = Data Engineering + ML + Software Engineering // Satish Chandra Gupta // MLOps Coffee Sessions #16
Related Questions