Sentiment Analysis Project

This project is a Sentiment Analysis application that classifies text into positive, negative, or neutral sentiments. It leverages Natural Language Processing (NLP) techniques and machine learning models to analyze opinions, reviews, or social media posts, providing valuable insights into user emotions and trends.

✨ Features

• Preprocessing of raw text (tokenization, stopword removal, lemmatization).
• Machine learning / deep learning–based sentiment classifier.
• Support for custom datasets.
• Visualization of sentiment distribution.
• Simple interface (CLI / Web UI / API, depending on implementation).

🛠️ Tech Stack

• Languages: Python
• Libraries/Frameworks: scikit-learn, NLTK / spaCy, TensorFlow / PyTorch (as applicable)
• Data: IMDb, Twitter, or custom dataset

🚀 Use Cases

• Analyzing customer reviews to improve products.
• Monitoring public sentiment on social media.
• Market research and brand reputation management.
• Enhancing chatbots and virtual assistants with emotion detection.