VERİM was founded in 2016 with the goal of becoming the leading center in data science through world-class, multidisciplinary research on challenging real-world problems. We work with the industry and public institutions to help them generate business value from data; to disseminate knowledge and know-how to the industry, academic institutions and other stakeholders. We provide accessible R&D support to the industry on challenging data analytics problems that often require an interdisciplinary approach.
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"Computer Vision" is a technology field that enables computers or digital systems to understand and interpret visual information by mimicking the functions of the human eye and brain. In this field, using machine learning and artificial intelligence techniques, the aim is for computers to perceive, analyze, and extract meaningful information from images, videos, and in-depth visual environments.
Machine learning aims to model a situation using past data, allowing it to label new data when it arrives with the learned system.
The purpose of data visualizations is to help people derive meaning from complex data by stimulating the sense of sight...
High-performance computing aims to use available hardware most efficiently for computations requiring large amounts of processing and applications where processing time is critically important.
The 'Big Data Industry Workshop' organized by the Sabancı University Data Analytics Application and Research Center (VERİM) took place on October 30, 2017, at the Sabancı University Sakıp Sabancı Museum.
The Data Science Summer School (VBYO), initiated in 2017 by faculty members from Sabancı University and Boğaziçi University, was held on September 7-8, 2019, under the roof of Sabancı University Data Analytics Research and Application Center (VERİM) at the Sabancı University campus.
VERİM aims to be a pioneering center that will conduct scientific studies in both core areas and interdisciplinary projects in data analytics, develop joint R&D projects with stakeholders from industry and public sectors, and organize training seminars and workshops for all stakeholders on data analytics.