Data Science Intern
Highlights
Worked in teams with daily sprints, meetings, and evaluations guided by a mentor.
Completed a project on Unsupervised Anomaly Detection in Healthcare Providers' Data using ML and DL techniques.
Achieved high model performance and deployed a Flask-based application for real-time anomaly detection.
UI/UX Intern
Highlights
As part of the evaluation process, designed a food delivery gamified section in the app, enabling users to play games while earning rewards, creating mutual benefits for users and the company.
Collaborated with the UI/UX team to create responsive Figma prototypes for app registration and landing pages.
Data Science Intern
Highlights
Analyzed credit risk (P1, P2, P3, & P4) using XGBoost, achieving an accuracy score of 82% after tuning.
Initially, Random Forest and Decision Tree models achieved 76% and 71% accuracy, respectively.
Amazon
Selected among the top 3k out of 81k+ applicants for the Amazon Machine Learning Summer School 2024, gaining insights into advanced ML topics through sessions with Amazon applied scientists.
IEEE
Presented the paper "Leveraging Advanced Deep Learning Techniques for Automated Dermatological Image Classification" at IEEE AESPC-2024, highlighting AI applications in healthcare.
Internshala
SmartInternz
C++ (including OOP concepts), Python libraries (ML and data analysis), AI/ML, UI/UX Design (Figma), Frontend Development (HTML, CSS), DBMS, SQL, Cloud Computing, Computer Networks, Operating Systems.