NLP-Sentiment-Classification

Natural Language Processing (NLP) project for sentiment analysis using machine learning and deep learning models.

Overview

This project performs sentiment classification on textual data using TF-IDF + traditional ML models (Naïve Bayes, RandomForest) and deep learning transformers (DistilBERT, GPT-2).

It includes:

• Data Preprocessing;
• Exploratory Data Analysis (EDA);
• DistilBERT;
• GPT-2 Text Generation
• Machine Learning Models;
• Deep Learning Models;

---

Features

--> Sentiment Analysis using classical ML and Transformer models
--> Data Preprocessing & Cleaning (TF-IDF, stopword removal, lemmatization)
--> EDA with WordCloud & Histograms
--> Model Evaluation with Accuracy, Precision, Recall, F1-score
--> GPT-2 based text generation based on sentiment context
--> Automated Training and Evaluation using Hugging Face Transformers