Sentiment Analysis of Customer Reviews

Tools: Python, Pandas, NLTK, Scikit-learn, Matplotlib, Seaborn

This project analyzes customer reviews to extract meaningful insights about sentiment and product perception. Using NLP techniques, the data is cleaned, tokenized, and vectorized before applying sentiment analysis and frequency analysis to identify the most common words and themes. The goal of this project is to demonstrate the ability to process unstructured text data and translate qualitative feedback into quantifiable insights. The visualizations highlight sentiment distribution and keyword frequency, providing a clear view of overall customer satisfaction trends.