Aviv Vromen
Aviv Vromen is an experienced ML and data infrastructure engineer with a strong background in Python. He is currently working at bluevine, where he has played a key role in the company's success in the financial technology sector. Prior to that, Aviv made a contributions as an algorithm developer at Rafael, focusing on complex multi-agent systems.
In his conference talk, Aviv aims to share his approach to using aggregated data in order to improve feature calculation.
Sessions
In the world of data-driven decision-making, creating features from aggregated data is a common practice. However, the naive approach of iterating over large historical datasets for each calculation can be inefficient and time-consuming. Enter our Aggregation Engine: a mechanism for optimizing this process, enabling the reuse of historical aggregative data and preventing redundant recalculations. Join us in this talk as we unveil our design for this Aggregation Engine, walk through our Python implementation, and discuss how it helped us reduce the amount of time and fetched data required for feature calculations.