a delightful machine learning tool that allows you to train, test, and use models without writing code

UCI compatible chess engine

Igel UI is the official app that allows you to easily interacte with igel from a simple UI instead of using the terminal.

Jupyter notebooks. Suplementary material for the book Computational Seismology, A Practical Introduction - Heiner Igel

IGEL OS is built on a highly secure Linux distribution. Properly deployed, IGEL OS is locked down to the configurations and applications defined via UMS Profiles. The Custom Partitions feature allows you to implement custom scripts, apps, or other files to one or a group of devices running the IGEL OS.

Powershell Module / Tools for the use with products of IGEL Technology GmbH (https://www.igel.de/)

IGEL OS is built on a highly secure Linux distribution. Properly deployed, IGEL OS is locked down to the configurations and applications defined via UMS Profiles. These scripts allow you to implement custom features.

IGEL terminal factory reset key

IGEL-Community Docs v02 (2023)

Docs, Resources, Scripts, Best Practises etc.

Building Your Own IGEL OS App with igelpkg .

IGEL: Inductive Graph Embeddings through Locality Encodings

Igel Ärgern game written in C

training

An IRC bot running on Erk

Igel Argern

IGEL's modified initramfs.

Repository for custom IGEL profiles to share amongst other IGEL fans

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This repository contains a docker implementation of Igels "Universal Management Suite" to manage Thin Clients.

Image Generator EAbstration Layer

AN UNRESTRICTED AI. No integrated Guardrails ever Legal (always) Its an ios and android app as well

This repository contains the sources for fine-tuning LoRA adapters for instructed news snippet generation in german language with the IGEL model.

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AI for the board game "Hase und Igel" (Software Challenge 2018)

Kotlin AI for the Softwarechallenge 2018 featuring the game "Hase und Igel"

PoC and vulnerability report for CVE-2025-47827.

Creates a Convolutional Neural Network that can detect and classify traffic signs in images. Data provided by J. Stallkamp, M. Schlipsing, J. Salmen, and C. Igel. The German Traffic Sign Recognition Benchmark: A multi-class classification competition. In Proceedings of the IEEE International Joint Conference on Neural Networks, pages 1453–1460. 2011

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No description available