This podcast episode highlights the transformative role of data science within the traditional energy sector, featuring insights from Bengsoon Chuah on navigating challenges like unstructured data and data labeling. By sharing his experiences with machine learning, user engagement, and tools like Argilla and DuckDB, he illustrates how iterative processes and active learning can significantly enhance model performance, ultimately paving the way for the future of AI and machine learning operations in resource-constrained environments.
