Text Classification using Natural Language Processing (NLP)

In this project, I developed a Natural Language Processing (NLP) model to classify text into different categories. The work included text preprocessing (tokenization, stop-word removal, lemmatization), vectorization using TF-IDF/word embeddings, and building machine learning and deep learning models for classification. The model achieved high accuracy and can be applied in sentiment analysis, spam detection, and topic categorization. This project highlights my skills in text preprocessing, feature engineering, and model training for NLP tasks.