Twitter Sentiment Analysis is a Machine Learning and Natural Language Processing (NLP) project

Twitter Sentiment Analysis is a Machine Learning and Natural Language Processing (NLP) project developed to analyze and classify sentiments from Twitter data. The system processes tweets and predicts whether the sentiment is positive, negative, or neutral using text preprocessing and machine learning techniques.

Project Features:

* Twitter Data Cleaning and Preprocessing

* Text Tokenization and Feature Extraction

* Sentiment Classification using Machine Learning Models

* Natural Language Processing (NLP) Techniques

* Data Visualization and Model Performance Evaluation

Technologies Used:

* Python

* Pandas & NumPy

* Scikit-Learn

* NLTK

* Matplotlib & Seaborn

This project demonstrates practical experience in NLP, sentiment analysis, text classification, and building AI models capable of understanding and analyzing social media data for business insights and decision-making.