Practical 1

Implement Feed-forward Neural Network and train the network with different optimizers and compare the results

Practical 2

Write a Program to implement regularization to prevent the model from overfitting

Practical 3

Implement deep learning for recognizing classes for datasets like CIFAR-10 images for previously unseen images and assign them to one of the 10 classes.

Practical 4

Implement deep learning for the Prediction of the autoencoder from the test data (e.g. MNIST dataset)

Practical 5

Implement Convolutional Neural Network for Digit Recognition on the MNIST Dataset

Practical 6

Write a program for the Implementation of a Generative Adversarial Network for generating synthetic shapes (like digits)

Practical 7

Write a program to implement a simple form of a recurrent neural network.

Practical 8

Write a program for object detection from the image/video