One-Shot Learning with Triplet CNNs in Pytorch

Generative Adversarial Networks in TensorFlow 2.0

Vanilla GAN and WGAN implementations in PyTorch on the FashionMNIST dataset

Fashion Mnist image classification using cross entropy and Triplet loss

A pipeline built on MetaFlow for training Fashion MNIST dataset using Pytorch, experiment tracking using MLFlow and model deployment using BentoML

image classification and manipulation in python machine learning on fashion mnist dataset

This repository contains an implementation of a Deep Convolutional Generative Adversarial Network (DCGAN) trained on the FashionMNIST dataset. The project aims to generate realistic images of clothing items using a GAN architecture. It includes model definitions, training scripts, and visualizations of generated images at various training stages.

A pytorch implementation of Densenet for FashionMNIST dataset

classification of fashion data(28 x28 greyscale image) into 10 classes.

No description provided.

This project uses an Autoencoder for dimension reduction on the Fashion MNIST dataset, which contains grayscale clothing images. The goal is to reduce the 784-dimensional images (28x28) to a 128-dimensional latent space while reconstructing the images. The performance is evaluated using the Structural Similarity Index (SSIM).

SLIIT 4th Year 2nd Semester Machine Learning Project

This project explores the use of a Generative Adversarial Network (GAN) to generate fashion images from the Fashion MNIST dataset. The generator creates fake images, and the discriminator distinguishes them from real ones. Performance is evaluated using Fréchet Inception Distance (FID) to assess the quality of the generated images.

Deep Learning Project on Diffusion Models for Image Generation

Une série de notebooks qui expliquent en détail comment fonctionnent les modèles de diffusion

Pytorch implementation of a denoising autoencoder.

A consortium of popular ML algorithms/concepts implemented in Python.

Fashion Image CNN Classifier using Keras

ML project for Content Based Image Recognition using Keras

This repo contains the PyTorch implementation of the paper 'Adversarial Training for Free!', which can be found here: https://arxiv.org/pdf/1904.12843.pdf

The project aims to use modern data science tools

FashionMNIST - Logistic regression

Benchmarking and comparative analysis of custom PyTorch linear layer variants against the standard PyTorch nn.Linear.

[WIP] corpus container

Comparing different learning rate schedulers on a reduced CNN using PyTorch and FashionMNIST.

No description provided.

Fashion Forward: CNN-based Clothing Classifier for Automated Product Tagging A PyTorch implementation of a convolutional neural network to classify FashionMNIST images into 10 garment categories.

A beginner-friendly deep learning project using TensorFlow and Keras, where I built a CNN model to classify flower images and an MLP model to classify Fashion MNIST clothing items. Includes training, evaluation, and prediction steps for both problems.

Fashion-Mnist classification

Application of Wasserstein Generative Adversarial Networks on Fashion MNIST using PyTorch