This project leverages Natural Language Processing (NLP) and Machine Learning to analyze and categorize the sentiment of comments on YouTube videos. By utilizing pre-trained models and sentiment analysis techniques, the tool automatically classifies comments as positive, negative, or neutral, providing valuable insights into audience reactions.

Key features:

Text Preprocessing: Cleans and prepares YouTube comments for analysis. Sentiment Classification: Uses machine learning models to classify the sentiment of each comment. Data Visualization: Displays sentiment distribution for deeper insights. Technologies used:

Python, NLTK, scikit-learn, TensorFlow, Flask This project demonstrates my skills in NLP, ML model integration, and building applications that process real-time data.