Giter Site home page Giter Site logo

tejastidke / classification-of-fashion-clothing-dataset-using-mlp Goto Github PK

View Code? Open in Web Editor NEW
1.0 1.0 0.0 475 KB

Classification into 10 categories of Fashion-Mnist Data "Hello-world" program for machine learning

Jupyter Notebook 97.22% Python 2.78%
machine-learning classification mlp-classifier mlp-regressor fashion-mnist pandas numpy mlp-network mlp github

classification-of-fashion-clothing-dataset-using-mlp's Introduction

HOW TO RUN:

pip install numpy
pip install pandas
pip matplotlib

gcc python3 my_fashion.py

----------------------------------------------------------------------------------------------------------------------------------------------------
Context
----------------------------------------------------------------------------------------------------------------------------------------------------
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. Zalando intends Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing splits.

The original MNIST dataset contains a lot of handwritten digits. Members of the AI/ML/Data Science community love this dataset and use it as a benchmark to validate their algorithms. In fact, MNIST is often the first dataset researchers try. "If it doesn't work on MNIST, it won't work at all", they said. "Well, if it does work on MNIST, it may still fail on others."
----------------------------------------------------------------------------------------------------------------------------------------------------
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.

    To locate a pixel on the image, suppose that we have decomposed x as x = i * 28 + j, where i and j are integers between 0 and 27. The pixel is located on row i and column j of a 28 x 28 matrix.
    For example, pixel31 indicates the pixel that is in the fourth column from the left, and the second row from the top, as in the ascii-diagram below.
----------------------------------------------------------------------------------------------------------------------------------------------------
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
----------------------------------------------------------------------------------------------------------------------------------------------------
    Each row is a separate image
    Column 1 is the class label.
    Remaining columns are pixel numbers (784 total).
    Each value is the darkness of the pixel (1 to 255)
----------------------------------------------------------------------------------------------------------------------------------------------------
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/
----------------------------------------------------------------------------------------------------------------------------------------------------

classification-of-fashion-clothing-dataset-using-mlp's People

Contributors

tejastidke avatar

Stargazers

 avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.