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 1 | # Keras-LSTM-Sentiment-Classification
 2 | Using Deep Learning Neural Networks to classify reviews of movie dataset to Positive and Negative Sentiment.
 3 | 
 4 | 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.
 5 | 
 6 | Requirements -
 7 | 1. Python 3
 8 | 2. Google word vectors (https://code.google.com/archive/p/word2vec/)
 9 | 3. Theano/Tensorflow (I have created model using Theano)
10 | 4. Keras (As a wrapper around Theano/Tensoflow)
11 | 
12 | Here we have used LSTM that are best RNN for doing text classification. Its a binary class problem i.e positive and Negative sentiment.
13 | I was able to get 90% accuracy. But we can improve it more my creating more complex model and tuning the hyper parameters.
14 | 
15 | 
16 | Just run Keras-LSTM-Sentiment-classification.ipynb notebook and check the results.
17 | Happy Learning.
18 | 


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