Sentiment Analysis Project

Overview

This project uses Natural Language Processing (NLP) and Machine Learning techniques to classify text sentiment.

The project demonstrates data preprocessing, text cleaning, TF-IDF vectorization, Logistic Regression, and model evaluation using Python.

Tools Used

• Python
• Pandas
• NLTK
• Scikit-Learn
• TF-IDF
• Logistic Regression

Skills Demonstrated

• Natural Language Processing (NLP)
• Text Classification
• Data Cleaning
• Feature Engineering
• Machine Learning
• Model Evaluation

Project Workflow

1. Load text dataset
2. Clean and preprocess text
3. Remove stopwords
4. Apply lemmatization
5. Convert text to TF-IDF features
6. Train Logistic Regression model
7. Evaluate performance

Future Improvements

• Compare additional ML models
• Experiment with word embeddings
• Deploy as a web application