Tweet Sentiment Analysis

🚀 A Natural Language Processing (NLP) project to classify tweets as positive, negative, or neutral using machine learning and deep learning techniques.

📌 Project Overview

This project analyzes the sentiment of tweets by leveraging Natural Language Processing (NLP) techniques. It classifies tweets into three categories:

✅ Positive

❌ Negative

😐 Neutral

🛠️ Features

• Preprocessing tweets (removing stopwords, punctuation, hashtags, mentions, etc.)
• Exploratory Data Analysis (EDA) with visualizations
• Feature extraction using TF-IDF & word embeddings
• Model training using Machine Learning (Logistic Regression, SVM , RandomForest , MultinomialNB)
• Performance evaluation

📌 Tech Stack

• Programming Language: Python 🐍
• Libraries: Pandas, NumPy, NLTK, Scikit-Learn
• Visualization: Matplotlib, Seaborn, WordCloud
• Models: Logistic Regression, SVM, MultinomialNB , RandomForest