To explore the life cycle of an application developed for Android devices from the perspective of a development methodology focused on the collaboration of different fields of study: medicine and ...engineering. The project consisted in the development of an application for android devices focused on the area of medicine, specifically on diabetes and its different variants. For this, a development team was assigned from the Catholic University of Colombia and a research team from the Technologic of Monterrey. The first section addresses the general aspects of the document to lead the reader to the understanding of the document in its completeness. The second section describes the development of the applications on Android devices as well as the technologies and tools used for the construction of the application; the third section discusses aspects of the applied work methodology with which the project was executed; the fourth section reflects on the soft skills necessary for the growth of software developers. The fifth section describes and shares the application in its current state and in the sixth part of the document there is a discussion about future applications and iterations of the application and the way of working.
Job Recommendation System using Machine Learning Gadegaonkar, Sakshi; Lakhwani, Darsh; Marwaha, Sahil ...
2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS),
2023-Feb.-2
Conference Proceeding
Millions of students graduate from college every year and start looking for jobs, but hunting for a suitable job that pays according to the applicant's skills is not an easy process. On the other ...hand, recruiters and companies look for graduates to join them according to their requirements. Unfortunately, there is often a gap between the applicants (job seekers) and recruiters (job providers). To bridge this gap and solve this problem, this study has come up with a job recommendation system that will recommend jobs in the IT sector that match the applicants' skills and expectations. This study has built an Android application to recommend jobs to the users based on their interests, databases, frameworks, platforms, and languages comfortable with. The recommendation is done by using a Machine Learning (ML) model (written in Python), which makes use of the content-based filtering algorithm. This study has built the application using Kotlin, Jetpack Compose, Ktor, and the UI has been designed by using Material 3 Design Principles.