#Sentiment Analysis in IMDB movie review dataset
::Sentiment analysis of IMDB Movie Review dataset with CNN::
Convolution with filter size 2,3,4.
Embedding -> Convolution -> max-pooling -> dropout -> Predictions -> Loss
Train examples = 22500 Validation examples = 2500 Embedding size = 128 Filter sizes = 3,4,5 Filters of each size = 128 Dropout keep_prob = 0.5
Epochs = 200
After 1500 steps, Train Accuracy = 100% Validation accuracy = 88%
Image courtesy:http://www.wildml.com/2015/11/understanding-convolutional-neural-networks-for-nlp/
::Sentiment analysis of IMDB Movie Review dataset with LSTM+RNN::
LSTM units = 10 Train examples = 22500 Validation examples = 2500 Embedding size = 128
After 200 steps, Training accuracy: 50%