Feed-forward neural network implementation in C with SIMD instructions

This repo contains my experiments with machine learning, specifically convolutional neural networks.

Fully Connected Neural Network, Numpy, Computational graph

Double Descent results for FCNNs on MNIST, extended by Label Noise (Reconciling Modern Machine-Learning Practice and the Classical Bias–Variance Trade-Off).

Fully connected neural network diagnosing patients with diabetes.

A fully connected linear neural network to recognize handwritten digits trained on the MNIST dataset

Fully Connected Forward Feed Neural Network

Implement GAN (Generative Adversarial Network) on MNIST dataset. Vary the hyperparameters and analyze the corresponding results.

Building fully connected neural network from zero without using deep learning libraries such as Pytorch.

Investigates which datasets different neural network implementations are useful

Unsupervised Learning Algorithms being implemented to detect a liar.

This GitHub repository contains the code used for CS-671: Introduction to Deep Learning course offered by IIT Mandi during the Even Semester of 2022. The repository includes the implementations of various deep learning algorithms and techniques covered in the course.