Implement a GAN for Fashion Mnist dataset to generate digits

A simple PyTorch implementation of conditional denoising diffusion probabilistic models (DDPM) on MNIST, Fashion-MNIST, and Sprite datasets

A Biologically-Inspired Approach to Continual Learning through Adjustment Suppression and Sparsity Promotion

This script outlines the implementation of a Generative Adversarial Network (GAN) designed to generate fashion images using the Fashion MNIST dataset. The GAN consists of a generator and a discriminator, which are trained simultaneously in an adversarial manner.

Scripts for downloading, preprocessing, and numpy-ifying popular machine learning datasets

Python from-scratch implementation of a Neural Network Classifier

Introduction to neural networks - from scratch.

Personal practice about image classification applied to Fashion Mnist dataset.

some neural networks implemented by burn framework

OCR project with MNIST and FASHION-MNIST datasets. A website allows you to take photo of handwritted numbers from which you can obtain a prediction of what this number is.

This code tackles the classic Fashion MNIST image classification task using TensorFlow and a multi-layer perceptron (MLP) neural network.

This repository contains Python code to classify fashion items using a Convolutional Neural Network (CNN) implemented with TensorFlow and Keras. It includes data preprocessing, model building, training, evaluation, and visualization of results.

Implementation of a Convolutional Variational Autoencoder in Flux.jl

Object recognition by random binary data lookup for Fashion MNIST

final project, classification base on tree data strucutures, random forest

ML project for two datasets House prices, and Fashion MSNIST

Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)

Fashion MNIST linear classification model with Keras 3.0 and PyTorch

Vogue GAN. Building a GAN in PyTorch from scratch!

Training a convolutional neural network to classify the Fashion MNIST Dataset