Demos for training different CNNs on the Fashion-MNIST dataset
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Updated
Aug 31, 2024 - Python
Demos for training different CNNs on the Fashion-MNIST dataset
This dataset, featuring an even distribution across genders and ages from various countries, is ideal for applications requiring detailed analysis of human postures, hairstyles, and different scenarios. With fine labeling of 19 human body areas, it facilitates advanced semantic segmentation tasks.
Build a GAN for the fashion industry
Exploration of various ML models and techniques for cognitive computing tasks. The primary focus is analysing hidden representations and the effectiveness in classifying data
Electric Soul
Train and Inference on Fashion Mnist dataset using TensorFlowJS
Implementation of a Multi-layer Perceptron classifier with hyperparameter tuning and k-fold cross-validation employing GridSearchCV for classifying images on the Fashion MNIST dataset 👗👚👖
Used normal neural networks and convolutional neural networks in many many data like animals, fashion, flowers classification, and also temperature predictions and time-series. Have fun. BTW used tensorflow for the works.
This repository contains a Jupyter Notebook that compares the performance of Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) architectures for image classification tasks using the Fashion MNIST dataset. The notebook explores the process of training CNN and RNN models
Personal practice about image classification applied to Fashion Mnist dataset.
Repository with deep learning examples. Please feel invited to contribute to the repository.
CNN for Fashion Mnist
A ANN Model is developed to classify the various fashion clothing items based of their images. A MNIST-like fashion product database.
Fashion-MNIST-Classification-using-Dense-Neural-Network addresses a classification problem on the Fashion MNIST dataset. With 60K training and 10K test samples of 28x28 grayscale images, the dataset spans 10 classes. Leveraging Keras, this project explores Dense Neural Networks using both Sequential and Functional APIs for efficient classification.
Use 2 different models and compare their performance on the Fashion-MNIST Dataset.
AutoEncoders -TF -Keras - Fashion_MNIST
Fashion MNIST is intended as a drop-in replacement for the classic MNIST dataset—often used as the "Hello, World" of machine learning programs for computer vision. The MNIST dataset contains images of handwritten digits (0, 1, 2, etc.) in a format identical to that of the articles of clothing you'll use here.
Experimental project that utilises a multi-class classification model to predict and categorise MNIST's fashion dataset
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