A comprehensive analysis of the Fashion MNIST dataset using PyTorch. Covers data preparation, EDA, baseline modeling, and fine-tuning CNNs like ResNet. Includes modular folders for data, notebooks, and results. Features CSV exports, visualizations, metrics comparison, and a requirements.txt for easy setup. Ideal for ML workflow exploration.

My solution for "Zalando's Fashion MNIST" challenge on dockerized Jupyter Notebook.

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

In this notebook, I build a classification model on the FashionMNIST dataset available in Keras.

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

This repository contains a Jupyter Notebook that explores various clustering techniques applied to the Fashion MNIST dataset like K-Means, Hierarchical,etc.