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Suyash Harlalka's Projects

cse-502n---data-structures icon cse-502n---data-structures

This has assignment solutions from data structures class that requires implementation of min heap, hash table, avl trees and Djikstra's shortest path algorithm

cse515t icon cse515t

Materials for Bayesian Methods in Machine Learning Course

generalised-neural-network icon generalised-neural-network

This is an implementation of fully connected neural network from scratch. Batch normalization, regularization using dropout , and momentum, SGD, and adam optimization techniques have been implemented.

generalized-convolutional-neural-network icon generalized-convolutional-neural-network

This repository contains an implementation of CNNs from scratch. It has dropout regularization, both for convolution and fully connected layers. It also has batch normalization implemented - both for fully connected and convolution layers. It takes the model characteristics as input from the user. This, currently has implementation for Conv + relu and Max pool layers in the convolution segment of the network. Also, final layer before fully connected segment is a max pool layer. This implementation makes use of functions from generalized-neural-network repository for the fully connected layer's computation.

nanogpt icon nanogpt

The simplest, fastest repository for training/finetuning medium-sized GPTs.

neural-style-transfer icon neural-style-transfer

This is an implementation of neural style transfer, which I wrote to generate a Van Gogh styled portrait of my friend, Eric, to give him as his "going away" present. This is motivated by post " Neural Style Transfer: Creating Art with Deep Learning using tf.keras and eager execution" . Theoretical basics were covered from Coursera lectures and Gatys et al.(2015) paper. Application using tensorflow and keras was done by referring to the referred post.

plugin-gui icon plugin-gui

Software for processing, recording, and visualizing multichannel electrophysiology data

resnet50-signs icon resnet50-signs

This has a detailed implementation of ResNet50 architecture from scratch in keras to identify signs of numbers

rnn---name-generation icon rnn---name-generation

This is a vanilla implementation to generate dinosaur names. Dataset was taken from Coursera's sequence model course. We can train it on any other data set of names to generate alike names.

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