Keras-LSTM-Sentiment-Classification

Using Deep Learning Neural Networks to classify reviews of movie dataset to Positive and Negative Sentiment.

We are using keras that act as a Wrapper on top of Theano/Tensorflow to create ML models easily as creating models using Theano or Tensorflow requires a lot of code to be written.

Requirements -

1. Python 3
2. Google word vectors (https://code.google.com/archive/p/word2vec/)
3. Theano/Tensorflow (I have created model using Theano)
4. Keras (As a wrapper around Theano/Tensoflow)

Here we have used LSTM that are best RNN for doing text classification. Its a binary class problem i.e positive and Negative sentiment. I was able to get 90% accuracy. But we can improve it more my creating more complex model and tuning the hyper parameters.

Just run Keras-LSTM-Sentiment-classification.ipynb notebook and check the results. Happy Learning.