HAPI Explorer: Comprehension, Discovery, and Explanation on History of ML APIs
DOI:
https://doi.org/10.1609/aaai.v37i13.27064Keywords:
MLaaS, Model Evaluation, Explainable ML, ML Visualization, ML DatasetAbstract
Machine learning prediction APIs offered by Google, Microsoft, Amazon, and many other providers have been continuously adopted in a plethora of applications, such as visual object detection, natural language comprehension, and speech recognition. Despite the importance of a systematic study and comparison of different APIs over time, this topic is currently under-explored because of the lack of data and user-friendly exploration tools. To address this issue, we present HAPI Explorer (History of API Explorer), an interactive system that offers easy access to millions of instances of commercial API applications collected in three years, prioritize attention on user-defined instance regimes, and explain interesting patterns across different APIs, subpopulations, and time periods via visual and natural languages. HAPI Explorer can facilitate further comprehension and exploitation of ML prediction APIs.Downloads
Published
2023-09-06
How to Cite
Chen, L., Jin, Z., Eyuboglu, S., Qu, H., Ré, C., Zaharia, M., & Zou, J. (2023). HAPI Explorer: Comprehension, Discovery, and Explanation on History of ML APIs. Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 16416-16418. https://doi.org/10.1609/aaai.v37i13.27064
Issue
Section
Demonstrations