SMS spam detection using Recurrent Neural Networks

Implementation details:
1. SMS dataset is taken, which is represented with ham and Spam
2. Dataset is pre-processed
a.removed all stop word, stop words are given in separate file
b. converted type of sms to numeric ham-1 and spam-2
3. Pre-processed dataset is tokenized, applied pad_sequnce, then converted to vectors
4. Then they are trained by network model and creates output file h5, json
5. Test input is given to the model and predicts the output
6. Comparison and accuracy are arrived.

Python Demo