This repository contains the implementation of various machine learning models for emotion detection from textual data. The project explores several approaches, including Support Vector Machines (SVM), Logistic Regression (LogReg), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), to analyze and predict emotions expressed in text.
Multiple ML Models: Implements SVM, LogReg, CNN, and RNN to detect emotions. Textual Emotion Analysis: Focuses on understanding the emotional context of written language. Comparative Analysis: Compares the performance of different models in emotion detection.