CS559-NeuralNetworks

A repository to showcase my learnings in Neural Networks and ability to code using frameworks like PyTorch. Obtained a grade of A (4/4).

Homework Description

1. HW1 - An introduction to creating a two-layer neural network.
2. HW2 - A python program to train weights using perceptron training algorithm with the step function.
3. HW3 - A python program to implement multicategory PTA for digit classification. The dataset was the MNIST dataset inspired by http://yann.lecun.com/exdb/mnist/.
4. HW4 - A python program to implement Backpropogation Algorithm to train a neural network for curve fitting.
5. HW5 - An introduction to PyTorch. Using PyTorch, a Convoluted Neural Network has been implemented for shape classification.
6. HW6 - A python program to implement an AutoEncoder followed by applying K-Means algorithm for digit classification. The AutoEncoder is implemented using PyTorch and K-Means algorithm is implemented using Scikit-Learn library.
7. HW7 - A python progam using PyTorch to implement a character-level text generation LSTM network.