This project focuses on analyzing textual data to automatically determine the sentiment expressed in user reviews, social media posts, or other forms of text. Using natural language processing (NLP) techniques, the model classifies text as positive, negative, or neutral. The workflow includes data preprocessing, feature extraction (like TF-IDF or word embeddings), and training machine learning models (such as Logistic Regression, Naive Bayes, or deep learning models like LSTM). The project demonstrates the ability to extract actionable insights from large volumes of text, providing businesses