Project Overview
Key Features: Built a machine learning pipeline for text preprocessing, tokenization, and model training. Designed a Flask-based web application with a user-friendly interface, allowing users to input text and instantly view predictions. Integrated sentiment visualization to provide meaningful insights into user inputs. Focused on ethical AI to address hate speech effectively.
Technologies Used: Python, TensorFlow, and Keras for deep learning model development. Flask framework for deploying the model as a web application. Kaggle dataset for training and evaluation. This project demonstrates expertise in deep learning, natural language processing (NLP), and web application development, showcasing practical implementation in real-world scenarios.