1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
Scalable End-to-End ML Platforms: from AutoML to Self-serve
Igor L. Markov, Pavlos A. Apostolopoulos, Mia R. Garrard +8
ML platforms help enable intelligent data-driven applications and maintain them with limited engineering effort. Upon sufficiently broad adoption, such platforms reach economies of…
cs.LG2021
Looper: An end-to-end ML platform for product decisions
Igor L. Markov, Hanson Wang, Nitya Kasturi +16
Modern software systems and products increasingly rely on machine learning models to make data-driven decisions based on interactions with users, infrastructure and other systems.…