My Numba works refined into a complete learning module

A simple Python vector addition project using Numba CUDA, demonstrating CPU vs GPU parallel computing. Compares sequential CPU vector addition with GPU-accelerated Numba implementation. Shows how to write GPU kernels with @cuda.jit, manage device memory, and compare CPU vs GPU performance.

A near-zero overhead AVL Tree for Python that bypasses object-heavy limits using JIT compilation and manual memory management.

A Python library for efficient feature ranking and selection on sparse data sets.

Parallelized direct N-body code in Python + Numba to simulate galaxy mergers with ~2×10⁵ particles

Adaptive control for skid-steer robots using GP-enhanced MPPI for robust navigation and obstacle avoidance on diverse terrains.

A high-performance, parallelized order book simulator with trace-level performance introspection using magic-trace. Designed for systems engineers and quant-minded developers.

Building upon original repo, trying to implement encoder-decoder transformer using CUDA

Plasma Particle Dynamics (PPDyn), a python code to simulate plasma particles using Molecular Dynamics Algorithm. Numba JIT compiler for Python has been implemented for faster performance. Detailed documentation can be found at https://ppdyn.readthedocs.io/.

Simulation of plant growth in 2D. Accelerated with Numba

Performance Comparison for Conway's Game of Life

QuantHedge-MM implements advanced computational methods for pricing and hedging options in markets with stochastic regime shifts. Built for quants and researchers, it extends Black-Scholes to Markov-modulated models.

This project implements a CNN from scratch using NumPy and Numba to recognize hand signs representing digits (0-9) from the Sing Language MNIST dataset.

A customized sparse solver wrapper with Numba compatibility

This repository contains a Python script that performs portfolio risk analysis on selected assets using Value at Risk (VaR) and Expected Shortfall (ES) measures. The script uses Numba to optimize the risk calculations, downloads historical data from Yahoo Finance with yfinance, and visualizes the portfolio's return distribution

Modern Portfolio Theory (MPT) and Monte Carlo simulations to optimize and backtest a portfolio of various financial assets

This is a tutorial about Numba-CUDA

This repository contains an advanced tutorial on optimizing Python code for machine learning applications, focusing on processing large amounts of data efficiently. It covers three powerful libraries: Numba, NumPy, and Polars.

Magnetic field visualization for ideal transmission line using Python.

A 2D Fractal Generator