Name: Deepak Rajkumar Sawalka
Type: User
Company: Northeastern University
Bio: Graduate Student | MSIS @Northeastern University | Data Enthusiast
Location: Boston, Massachusetts
Deepak Rajkumar Sawalka's Projects
Developed a recommendation system to enhance the Amazon FBA product selection process and utilized machine learning techniques, to identify key trends to make accurate product recommendations.
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Software designed to identify and monitor social/historical cues for short term stock movement
Created a dashboard that leverages customer data to extract valuable insights and performed various unsupervised machine learning algorithms. By identifying groups of customers with similar characteristics, the dashboard enables companies to tailor marketing strategies for each group, leading to increased revenue and business growth.
Developed a emotion recognition system using controlled AI and OpenCV, which utilizes dlib library for face detection and Deepface library for emotion recognition. By capturing screenshots of Google Meet sessions, the system predicts emotions ,provides valuable insights for teachers to adapt their teaching methods to their students emotional states
Built a Hospital Management System using Java Swing an application that can be used to manage the day-to-day operations of a hospital. The system allows users with different admin roles to perform different tasks based on their level of access. The system includes CRUD operations which are fundamental to manage any data-driven applications.
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Developed a transportation database system, specifically for the Northeastern Community which will assist students, faculty, and other community members to reach their destinations promptly and safely regardless of the time using different modes of transport viz. cabs, buses, trams, cycle, or walking
Developed an Education Consultant System using Java Swing, which is a comprehensive platform that is designed to streamline the education consulting process and make it easier for students and education consultants to connect and work together. It includes advanced features such as integration of Google Maps, E-mail , and Role-based access control.
Developed a system for autonomous vehicles to identify & classify traffic signs in real time, enhancing road safety and driver decision making. Built a CNN model, a deep neural network, to classify images into their respective categories and achieved 95% accuracy
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