Progyan's Projects
Bishop is a work-in-progress neural operator library in C++.
Part of the MA 201 project on the Black-Scholes equation, by Progyan Das, Vedang Chavan, Rahul Chembakasseril, Yash Kokane, and Shaandili Vajpai
A visual introduction to probability and statistics.
A Windows-based python application aimed at putting Wikipedia at the tip of your finger. One finger.
A temporal GNN based model for climate data.
Constructing an open-source library like NLTK and spaCy for efficient processing of code-mixed text, models, and datasets under Prof. Mayank Singh.
Library for analysing, backtesting, and presenting cryptocurrency portfolios reliably, and with very little code.
A code-mixed annotation tool aimed at increasing the annotation quality whilst reducing the annotation time and various overheads associated with code-mixed data.
My first foray into competitive coding. The commit structure journals my daily improvement!
Assignments submitted as part of Computer Architecture Course
Assignments done as part of auditing the CS229 course offered by Stanford in 2018, by Professor Andrew Ng. An abridged version of the course is available on Coursera.
š A visualization of Craig Reynold's Boids
An implementation of Fourier Epicycles, with a twist.
Gossip is a beautiful tree-walk interpreter (that now also supports bytecode!) that allows for beautiful visualizations for abstract syntax trees, and is built to support beginners starting a course on Compiler Design.
A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably including Stochastic Variational Gaussian Processes.
A didactic Gaussian process package for researchers in Jax.
Official Students App for IITGN!
The official repository of IRP 2022-23.
Addictive Reinforcement Learning
CS 432
Some challenge solutions solved using z3
A simple program to simulate attraction/reuplsion forces between many particles
Template repository for working on openGL with macOS.
roses are red this page is neat, lmao yeet
Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.