Master’s Projects Experience
📱 iPhone Issues Identification and Interpretation
The “iPhone Issues Identification and Interpretation” project analyzes user-generated content from subreddits to identify iPhone-related issues. It uses sentiment analysis, topic modeling with BERTopic, and LLMs like fine-tuned BERT and Mistral AI to extract topics, interpret issues, and provide data-driven insights.
✨🎓 Academic Ally: Course Recommendation Chatbot
This is an AI-powered course recommendation chatbot that provides personalized course suggestions based on user interests and goals. This Streamlit application uses advanced natural language processing and retrieval techniques to offer tailored educational recommendations.
🚦 Traffic Sign Identification
This project aims to develop a Traffic Sign Classifier to recognize various traffic sign categories using a labeled dataset of images. The project incorporates a comparative study of fine-tuning strategies for the classification model by exploring the performance difference approaches.
✌️ 10 Sign Languages Representing 0 to 9
The goal of this project is to build a machine learning model that can detect and classify digit hand signs from images. The model is trained to recognize the digits 0 through 9 based on hand gestures.
😊 Face Emotion Classification
This project aims to classify human emotions from facial expressions using a deep learning model. The model is trained to recognize seven different emotions: angry, disgust, fear, happy, neutral, sad, and surprise. Using a convolutional neural network (CNN) architecture, the model processes images of faces and predicts the corresponding emotion.
🌪️ Disaster Tweets Classification
Natural Language Processing with Disaster Tweets Predict which Tweets are about real disasters and which ones are not.