N

neural network

The efficient alternative to Neural Networks. Implements SLRM (Segmented Linear Regression Model) for neural compression and non-linear data modeling, achieving high precision with a fraction of the parameters of a traditional ANN.

Extract video representations (semantic, geometric, deep features) for the frames of any video.

AZ-Lite is a compact, AlphaZero-inspired chess engine written in Python. It combines Monte Carlo Tree Search (MCTS) with a lightweight policy-and-value neural network, learning entirely through some self-play.

This repo will have all resources, labs, data which I use/d on Kaggle Network

A simple multilayer perceptron (MLP), also known as a fully connected feedforward artificial neural network, written from scratch in Julia.

Lightweight C library for creating, training, and evaluating simple neural networks

SYNTHESIS is an experimental algorithm that visually represents the emergent behavior of a synthetic neural network — an abstraction of how organic life and thought might arise from simple computational interactions.

Inspired by Conway’s Game of Life, this project explores how randomness, local interactions, and algorithmic feedback can generate the illusion of living, thinking patterns.

Just me learning ML.

Predicting digit labels (0–9) from the MNIST dataset using Keras neural network.

A neural network-based differential equation and variational problem solver

https://elvet.gitlab.io/elvet/

A Python Library for Physics-Informed Neural Networks

A desktop user interface for upscaling images using waifu2x-ncnn-vulkan

⚠️⚠️⚠️ NOT WORKING YET ⚠️⚠️⚠️

UI Demo (non-functional) via GitLab Pages: https://zoomer-c4a624.gitlab.io/

This project provides several implementations that can be used to analyze Hessians associated with synthetic and empirical loss functions.

This is an implementation of a very simple neural network from scratch.

This is a project that implements a simple neural network.

Neural Network for MicroPython

rust implementation of KAN

An example of tabular data regression (parameter estimates) using TabNet