Machine learning is being widely adapted in industrial applications owing to the capabilities of commercially available hardware and rapidly advancing research. Volkswagen Financial Services (VWFS), as a market leader in vehicle leasing services, aims to leverage existing proprietary data and the latest research to enhance existing and derive new business processes. The collaboration between Information Systems and Machine Learning Lab (ISMLL) and VWFS serves to realize this goal. In this paper, we propose methods in the fields of recommender systems, object detection, and forecasting that enable data-driven decisions for the vehicle life-cycle at VWFS.
翻译:由于具备商业硬件和迅速推进的研究的能力,机器学习正在工业应用中被广泛应用,大众金融服务公司作为车辆租赁服务市场的领导者,旨在利用现有的专有数据和最新研究,加强现有的和新的业务流程。信息系统和机器学习实验室(ISML)与VWFS之间的合作有助于实现这一目标。我们在本文件中提出了推荐系统、物体探测和预测等领域的方法,以便能够在VWFS车辆生命周期方面作出由数据驱动的决定。