Framework and Language for Neurosymbolic Programming.
-
Updated
Jun 26, 2026 - Rust
Framework and Language for Neurosymbolic Programming.
A software engineering framework to jump start your machine learning projects
TwinGraph is a Python framework for distributed container orchestration using Kubernetes clusters, Docker Compose/Swarm or cloud resources on AWS (AWS Lambda, AWS Batch, Amazon EKS). Applications include high-throughput simulations, simulation-driven optimization, Digital Twins and machine learning.
A tiny deep neural network framework developed from scratch in C++ and CUDA.
A curated list of awesome Machine Learning frameworks, libraries and software.
A modern educational deep learning framework for students, engineers and researchers
Mythral Neurosymbolic AI
🏄 A Lightweight Web Browser-based Machine Learning Framework
A Machine Learning library that allows users to create their own datasets and use models without having to write too much code. Built with Python.
CTorch is a super lightweight C implementation of PyTorch, built for learning and exploration. It's a "just for fun" project to dive into understanding the basics of machine learning frameworks.
Pure C training framework featuring a modular Trainer, DataLoader, SGD/Adam optimizers, learning-rate scheduling, callbacks, evaluation metrics, checkpointing, and end-to-end model training built from scratch.
Machine learning framework for Rust
This repository serves as a comprehensive showcase of my skills and expertise in data science, encompassing various projects and exercises completed throughout the bootcamp.
Docker image used in Apolo Platform Template with pre-installed ML frameworks
Neural network framework implemented from "scratch" with Python and Numpy for matrix operations
MarioPPO implementation uses the TensorFlow machine learning platform
Super Simple AI framework!
Add a description, image, and links to the machine-learning-framework topic page so that developers can more easily learn about it.
To associate your repository with the machine-learning-framework topic, visit your repo's landing page and select "manage topics."