https://github.com/sushantdhumak/fashion-clothing-classification

Kaggle Machine Learning Competition Project : In this project, we will create a classifier to classify fashion clothing into 10 categories learned from Fashion MNIST dataset of Zalando's article images
https://github.com/sushantdhumak/fashion-clothing-classification

adam-optimizer categorical-cross-entropy classification classification-report conv2d dropout keras keras-classification-models keras-neural-networks maxpooling model-evaluation reshaping splitting subplots

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Kaggle Machine Learning Competition Project : In this project, we will create a classifier to classify fashion clothing into 10 categories learned from Fashion MNIST dataset of Zalando's article images

• Host: GitHub
• URL: https://github.com/sushantdhumak/fashion-clothing-classification
• Owner: sushantdhumak
• Created: 2019-11-21T16:51:54.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2019-11-21T16:59:15.000Z (about 5 years ago)
• Last Synced: 2025-01-01T18:34:24.085Z (30 days ago)
• Topics: adam-optimizer, categorical-cross-entropy, classification, classification-report, conv2d, dropout, keras, keras-classification-models, keras-neural-networks, maxpooling, model-evaluation, reshaping, splitting, subplots
• Language: Jupyter Notebook
• Homepage:
• Size: 6.59 MB
• Stars: 7
• Watchers: 1
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Fashion-Clothing-Classification

## Kaggle Machine Learning Project

To create a classifier to classify fashion clothing into 10 categories based on Fashion MNIST dataset

### Disclaimer:

The given solutions in this project are only for reference purpose. 

### Kaggle Competition Link:

https://www.kaggle.com/zalando-research/fashionmnist

### Description of experiment

Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes

### Content

Each image is 28 pixels in height and 28 pixels in width, for a total of 784 pixels in total. Each pixel has a single pixel-value associated with it, indicating the lightness or darkness of that pixel, with higher numbers meaning darker. This pixel-value is an integer between 0 and 255. The training and test data sets have 785 columns. The first column consists of the class labels (see above), and represents the article of clothing. The rest of the columns contain the pixel-values of the associated image.

### Labels

Each training and test example is assigned to one of the following labels:

0 T-shirt/top 


1 Trouser 


2 Pullover 


3 Dress 


4 Coat 


5 Sandal 


6 Shirt 


7 Sneaker 


8 Bag 


9 Ankle boot

### Acknowledgements

Original dataset was downloaded from https://github.com/zalandoresearch/fashion-mnist

Dataset was converted to CSV with this script: https://pjreddie.com/projects/mnist-in-csv/