Project: Emotion Detection from Text

Team :

• Navnith
• Pragya
• Piyush
• Harsh Gupta

Highlights:

• This is a multi-class text classification (sentence classification) problem.
• The purpose of this project is to classify emotions from sentences into 7 different categories.
• The model was built with Convolutional Neural Network (CNN) and Word Embeddings on Tensorflow.

Train:

• To run CNN for classifcation -- Command: python train_cnn.py

• To run LSTM for classification -- Command: python lstm.py

  A directory will be created during training, and the best model will be saved in this directory.

Reference:

• Implement a cnn for text classification in tensorflow
• UNDERSTANDING CONVOLUTIONAL NEURAL NETWORKS FOR NLP
• Understanding LSTM for text classification

In order to run this download Word2Vec and Glove Vectors, since the file sizes are very large.

• [Glove] (https://nlp.stanford.edu/projects/glove/)
• [Word2Vec] (https://radimrehurek.com/gensim/models/word2vec.html)