Mood Classification using Python

Developed a Python-based Mood Classification system using machine learning algorithms to analyze and categorize text data based on emotional states. Utilized natural language processing (NLP) techniques and sentiment analysis to classify text inputs into predefined mood categories such as happy and sad. Implemented feature engineering, model training, and evaluation using libraries like NLTK, Scikit-learn, and TensorFlow to achieve accurate mood classification results.