Solving the Traveling Salesman Problem using Self-Organizing Maps

🔴 MiniSom is a minimalistic implementation of the Self Organizing Maps

NeuPy is a Tensorflow based python library for prototyping and building neural networks

Self organizing Kohonen map in Python with periodic boundary conditions

🌐 Deep Embedded Self-Organizing Map: Joint Representation Learning and Self-Organization

SuSi: Python package for unsupervised, supervised and semi-supervised self-organizing maps (SOM)

Python implementation of the Epigenetic Robotic Architecture (ERA). It includes standalone classes for Self-Organizing Maps (SOM) and Hebbian Networks.

Recursive Self-Organizing Map/Neural Gas.

Pytorch implementation of Self-Organizing Map(SOM). Use MNIST dataset as a demo.

🌐 SOMperf: Self-organizing maps performance metrics and quality indices

Using Self-Organizing Maps for Travelling Salesman Problem

FlowSOM algorithm in Python, using self-organizing maps and minimum spanning tree for visualization and interpretation of cytometry data

Compression of an image by Self organizing map.

Python machine learning library using powerful numerical optimization methods.

XPySom-dask is a minimalistic implementation of batch Self Organizing Map algorithm using Dask. This is a mirror of the original XPySom.

A mesh generator using machine learning.

ROS 2 packages to facilitate the integration of hardware acceleration capabilities in Xilinx's Kria SOM portfolio

In this project I write SOM(Self-Organazing-Map) Algorithm for Character recognition(There was 7 character and for each one 3 different example in train data). this Algorithm is competitive Algorithm, for example in this problem we define 7 random point (same dimension with characters) and in each iteration we find the nearest character to this …

A Python implementation of the Directed Batch Growing Self-Organizing Map