Neural Networks and Deep Learning (NNDL) Lab

This repository contains the implementation of some basic neural networks and deep learning algorithms as part of NNDL lab work. The list of topics are as follows:

1. Lab_01: Realization of Logic Gates and Linear Regression
2. Lab_02: Multi Class Classification using Perceptron
3. Lab_03: Associative Networks
4. Lab_04: Multi Layered Neural Networks and Backpropagation
5. Lab_05: Convolutional Neural Networks Part 1
6. Lab_06: Recurrent Neural NetworkAssignment
7. Lab_07: Image Classification using convolutional neural network
8. Lab_08: Autoencoders
9. Lab_09: Transformers
10. Lab_10: Restricted Boltzmann Machine
11. Lab_11: Generative Adversarial Networks

The Folder contains the following files:

• Skeleton notebook file (*.ipynb)
• PDF version of skeleton notebook file (*.pdf)
• Additional datasets if used in notebook
• Solution notebook file (*_Solution.ipynb)