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This repository provides a collection of machine learning algorithms implemented using pure numpy, useful for vibe coders working with AI tools.
PowerShell implementation of CVE-2021-1675 Print Spooler Local Privilege Escalation (PrintNightmare)
A simple PyTorch implementation of the Transformer model, useful for AI/ML developers.
An unofficial Keras implementation of the Noise2Noise image denoising algorithm, useful for vibe coders working with AI-powered tools.
Official implementation of SAM-Med2D, a tool for medical image segmentation using transformers.
SMAA is a GPU-based MLAA implementation for efficient anti-aliasing in games and graphics applications.
A powerful shell implemented by Vim, providing a robust and customizable terminal experience for developers.
An immutable radix tree implementation in Go, useful for high-performance key-value storage and lookup.
A fast and efficient C-based implementation of the Aho-Corasick algorithm for pattern matching and string manipulation.
A Go library for SAML authentication and service provider implementation.
An official implementation of a system for improving video understanding and generation with better captions.
An implementation of the Raft distributed consensus protocol using the Rust Tokio framework.
C# implementation of the PowerView framework for Windows domain enumeration and lateral movement
A minimal implementation of the Flash Attention algorithm in CUDA for efficient AI model inference.
A PyTorch implementation of the original Transformer model with interactive visualizations.
A PyTorch implementation of Temporal Segment Networks (TSN) for video understanding and action recognition.
A pure Swift implementation of UIKit that supports cross-platform development, including Linux.
Implementation of SegNet, a deep convolutional encoder-decoder for semantic pixel-wise labeling.
This repository provides a comprehensive guide and implementations for data algorithms using MapReduce, Spark, Java, and Scala.
HYPIR is a Python library for image restoration and super-resolution using diffusion-based priors.
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