We present an AutoML system called LightAutoML developed for a large European financial services company and its ecosystem satisfying the set of idiosyncratic requirements that this ecosystem has for AutoML solutions. Our framework was piloted and deployed in numerous applications and performed at the level of the experienced data scientists while building high-quality ML models significantly faster than these data scientists. We also compare the performance of our system with various general-purpose open source AutoML solutions and show that it performs better for most of the ecosystem and OpenML problems. We also present the lessons that we learned while developing the AutoML system and moving it into production.

翻译：我们介绍了一个名为LightAutomoML的自动ML系统,该系统是为一家大型欧洲金融服务公司开发的,其生态系统满足了该生态系统对于自动ML解决方案的一套特殊要求。我们的框架在很多应用中进行试点和部署,并在有经验的数据科学家一级进行,同时建立高质量的ML模型比这些数据科学家快得多。我们还将我们系统的绩效与各种通用开放源自动ML解决方案进行比较,并表明它对于大多数生态系统和开放ML问题都表现得更好。我们还介绍了我们在开发自动ML系统并将其投入生产过程中汲取的教训。