LLM training in simple, raw C/CUDA
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A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch
Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.
Minimal, clean code for the Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization.
NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.
Make videos on the computer you already own. FreeVideo runs MiniMax H3 in as little as 8 GB of VRAM and 16 GB of RAM, and adapts its acceleration path to your hardware.
Artificial Intelligence framework for games based on libGDX or not. Features: Steering Behaviors, Formation Motion, Pathfinding, Behavior Trees and Finite State Machines
- libgdx
- pathfinding
- steering-behaviors
- formation-motion
Robotics with GPU computing
DotRecast - a C# port of Recast & Detour, Industry-standard navigation mesh toolset for .NET, Unity3D, games, servers
- detour
- recast
- navmesh
- pathfinding
Vulkan, OptiX and CUDA Interoperation Modular Rendering Library and Framework for PC/Linux/Android
- vulkan
- raytracing
- graphics-engine
- graphics-library
Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.
- histopathology-images
- microscopy
- sliding-windows
- medical-image-analysis
Ruby library for interfacing with FANN (Fast Artificial Neural Network)
- ai
- ruby-fann
- ruby-gem
- neural-network
Tools for computational pathology
- machine-learning
- digital-pathology
- computational-pathology
- biomedical-image-processing
CellViT: Vision Transformers for Precise Cell Segmentation and Classification
- ai
- cell
- digitalpathology
- microscopy
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.
- artificial-intelligence
- clip
- pathology
- vision-and-language
Fusing Histology and Genomics via Deep Learning - IEEE TMI
- pathomic
- fusion
- multimodal
- pathology
AI-based pathology predicts origins for cancers of unknown primary - Nature
- histology
- pathology
- wsi-images
- histopathology
⚡ Open-source software for deep learning-based digital pathology
- deep-learning
- machine-learning
- digital-pathology
- computational-pathology
A foundation model-driven whole slide image-scale cell phenotyping method with QuPath integration Resources
- bioimage-analysis
- cell-classification
- computer-vision
- digital-pathology
🗺️ Developer Roadmaps — 20 career paths, 870+ topics, 1,880+ free resources. PWA, certifications, community-driven. Your free guide from beginner to senior dev.
A library for A* pathfinding. Written for easy integration and plug-and-play
- pathfinding
- pathfinding-algorithm
- algorithms
- artificial-intelligence
Dijkstra algorithm solution in GameMaker (Studio 2) to find shortest path in graph between two points.