Semester of Graduation
First Major Professor
Second Major Professor
Master of Science (MS)
Machine learning has recently gained popularity in many engineering, science, medical and other domains outside computer science. Therefore, many researchers, scientist, students and developers are developing machine learning based applications for various purposes. However, due to a large number of technologies and application deployment platforms, these professionals spend more time learning technologies than on developing and optimizing the core logic for their applications. This paper describes the design and implementation of a new cloud-based deployment platform suitable to deploy machine learning based applications across multiple platforms. This platform focuses heavily on security, privacy, and ease of deployment for developers. It enables developers to define the application logic in any programming language without worrying about performance, scalability and other deployment-related issues. This paper further demonstrates how to develop these applications by migrating the Rigid Pavement Analysis Tool developed by Prof. Halil Ceylan and his team.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.
Gore, Tanmay, "Cloud Migration of RPAT Tool" (2019). Creative Components. 182.