Emotion Detection & Sentiment Analysis System

Designed and implemented a machine learning system to detect emotions and analyze sentiment from text data.

The project focuses on extracting meaningful emotional patterns from user-generated content and classifying them into sentiment categories.

Key contributions:
• Preprocessed and cleaned text datasets for analysis
• Implemented NLP techniques for feature extraction
• Trained and evaluated machine learning models for emotion classification
• Analyzed accuracy and limitations of different models
• Documented insights and results for real-world use cases

Technologies used:
Python, Machine Learning, NLP, Data Analysis