Device Model Recommendation System Using Machine Learning

  • Jagruti Deshpande, Deepshree Kadus, Seema Pawar, Krutika Padeer, Sakshi Mandke


Recommendation systems are used to suggest relevant items to users. Recommendation system is a relatively new area of research in machine learning and is playing an important role in business growth. Today, every organizations have their IT administration teams to monitor and maintain the company’s computer infrastructure. There is requirement of suitable computer models for the company employees depending on the applications that they are working on and the memory usage that is required. The consequences of less suitable computer systems causes slow performance and inefficient work. Hence, there is a need of using appropriate computer systems to enhance work quality of the IT workforce. This paper proposes an idea to build recommendation system to recommend right model of devices to the IT team according to the running applications and memory usage using machine learning algorithms like K Nearest Neighbor, K means clustering and collaborative filtering approach. Analysis is done on the result to help the organizations for cost predictability of devices. This system can help organizations to get the suitable model of laptop or desktop with adequate computing power to increase IT efficiency and user productivity.