1) SimpleRNN
This is a simple RNN, a recurrent neural network whch does time series prediction. Given some set of input data, it is able to generate a prediction for the next time step.
This RNN is used to detect the sentiment in a given moview reivew. Given a movie review as an input, it classifes the review as positive or negative. It used LSTM, Long Short Term Memory to perform the analysis.
3) MNIST GAN
This is a GAN, Generative Adverserial Network used to generate hand written digits. It consists of a a discriminator neural network trained on the MNIST Handwritten digits dataset and a generator neural network which generates new images. If the image is classified as a hand written digit by the discirminator, then we have a digit successfully generated by the GAN.
This is a RNN which generates sentences character by character after being trained on a input text which in this case is Percy Jackson and the Last Olympian. It requires an input prime, which can be a single string or a collection of strings and generates sentences using those word/s.
5) Diner Dash using reinforcement learning
Diner dash is a game in which the player has to run a restaurant in a way to keep maximum customers happy. This is an attempt to play the game using reinforcement leanring using Stable Basline functions. This solution uses ACER(Actor-Critic with Experience Replay).