NAME

RAMINENI,PARDHA SARADHI

CLASS ID

32

IN CLASS PROGRAMMING

1. Add one more hidden layer to autoencoder

2. Do the prediction on the test data and then visualize one of the reconstructed version of that test data. Also, visualize the same test data before reconstruction using Matplotlib

3. Repeat the question 2 on the denoisening autoencoder

4. plot loss and accuracy using the history object

IMPLEMENTATION

We added one more hidden layer in the given source code of Autoencoder and predicted the value for the test data.

We plotted the input data and the reconstructed version of the image using the Matplotlib.

We implemented the same for the Denoisening Auto encoder in which we incorporated a noise of 0.5 to the input data and plotted the noisy version of input data and also the reconstructed version of data.

Finally we plotted the loss and accuracy curve for both the Encoders.