Prithvi Prakash's repositories
Channel-Specific-Autoencoder
This is an implementation of my research idea: A Channel-Specific Autoencoder inspired from the principle of "Co-operation" and "division of labour".
Autoencoder
A 5+5-layered Auto encoder that makes use of the LFW dataset to reconstruct facial images.
Face-Recognizer
This is a Face Recogniser, that uses logistic regression to solve the problem
image_pyramid
Implementation of Gaussian and Laplacian Pyramids
2024_Quandela_Remote
Quandela iQuHACK 2024 Remote Challenge
Algorithms
A repository of all the DS+A Problems I've worked on.
ModCom
ModCom (Model-Commodities) is a project intended to model the rise and fall of various commodity prices in the numerous markets of India, and identify profitable markets and supply-chain pipelines.
Normal-Equations
This Notebook explains in detail the Normal Equation that is made use of in Linear Regression
SwitchPointEncryption
A Proof of Concept for SwitchPoint Encryption.
BreakingCaesar
This Algorithm breaks the Caesar cipher. Reasonably high success rate.
CS229
A repository for all the problem sets of CS229
DigitRecogniser
This project works on building a training algorithm to recognise digits
HoneyEncryption
A web app for implementing honey encryption written using python for honey encryption modules, Django for backend purposes, bootstrap for front end development. This Honey Encryption algorithm provides resilience towards brute force attack which is one of the mazor threat for any encryption methods
KeenASR-Android-PoC
A proof-of-concept app using KeenASR SDK on Android. WE ARE HIRING: https://keenresearch.com/careers.html
Neural-Networks-Research
An implementation of a vanilla feedforward neural network
Stanford-ml-ex1
This is a set of all solutions of the Stanford Machine Learning Class' First Exercise.
Stanford-ml-ex2
All Solutions of the second excercise
Stanford-ml-ex3
An implementation of the representation of Neural Networks, with pre-trained weights.
Stanford-ml-ex4
More on Neural Networks: Training.
Stanford-ml-ex5
The fifth Exercise of the Stanford Machine Learning Course. Observing Bias and Variance
Stanford-ml-ex6
An implementation of Support Vector Machines
Stanford-ml-ex7
An implementation of Unsupervised Learning, and PCA
Stanford-ml-ex8
An implementation of an Anomaly Detector and a Recommender System
sunny1110.github.io
My Home Page.
Test
This is a test repository. I'm using it to test out my work.
Test3
My GitHub's giving me trouble. I'm using this to test if there's something wrong. Nothing of interest here.