/TweetClassificationLSTM

This project details the creation of a multi-classification Recurent Neural Network (RNN) model using Tensorflow / Keras to predict Tweet emotions. More specifically, this notebook uses a bidirectional LSTM as a means to capture additional semantics often found in sequential (language) data. This project utilizes the Tweet Emotion Recognition with TensorFlow dataset provided by Kaggle.

Primary LanguageJupyter Notebook

Twitter NLP Sentiment Multi-classification Model with a Long Short-Term Memory (LSTM), Bidirectional Recurrent Neural Network (BRNN) using Keras & TensorFlow

This project details the initial creation of a multi-classification Recurent Neural Network (RNN) model using Tensorflow / Keras to predict Tweet emotions. More specifically, this notebook uses a bidirectional LSTM as a means to capture additional semantics often found in sequential (language) data. This project utilizes the Tweet Emotion Recognition with TensorFlow dataset provided by Kaggle.