Write a python script using keras to train a fully-connected feed-forward neural network classifier to classify documents in the Amazon corpus into positive and negative classes. Your network must...

Write a python script using keras to train a fully-connected feed-forward neural network classifier to classify documents in the Amazon corpus into positive and negative classes. Your network must consist of: 1. Input layer of the word2vec embeddings you prepared in Assignment 3. 2. One hidden layer. For the hidden layer, try the following activation functions: ReLU, sigmoid and tanh. 3. Final layer with softmax activation function. 4. Use cross-entropy as the loss function. 5. Add L2-norm regularization. 6. Add dropout. Try a few different dropout rates.For this assignment, you must use your training/validation/test data splits from Assignment 1. Train your models on the training set. You may only tune your models on your validation set. Once the development is complete, run your classifier on your test set.