https://github.com/agamiko/tiny-mnist-challenge

Tiny MNIST Challenge for university student's class with example codes in matlab and pytorch.

https://github.com/agamiko/tiny-mnist-challenge

Science Score: 10.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
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  • Committers with academic emails
    1 of 8 committers (12.5%) from academic institutions
  • Institutional organization owner
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  • Scientific vocabulary similarity
    Low similarity (4.4%) to scientific vocabulary

Keywords

challenge convolutional-neural-network example-code pytorch student-project toolbox tutorial

Keywords from Contributors

data-augmentation audio-augmentation augmentation-policies autoaugment data-generation data-synthesis generative-adversarial-network graph-data-augmentation image-augmentation nlp-augmentation
Last synced: 5 months ago · JSON representation

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Tiny MNIST Challenge for university student's class with example codes in matlab and pytorch.

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challenge convolutional-neural-network example-code pytorch student-project toolbox tutorial
Created almost 6 years ago · Last pushed almost 6 years ago
Metadata Files
Readme License

README.md

Tiny MNIST Challenge 2020

Tiny MNIST Challenge for Gdańsk University student's class.

Kaggle: https://www.kaggle.com/c/msi-tinymnist2020

Matlab examples - code and toolboxes instruction.

Built-in data loaders and submission preparation. * Simple neural network - A framework for using matlab toolbox to design basic fully-connected network. code

  • Basic convolutional neural network - Simple neural network with 2 convolutional layers, relu activation, maxpooling and fully-connected layer.code

Pytorch examples - ready to run in Colab

Built-in data loaders, submission preparation and sending.

  • Simple neural network - This is a basic fully-connected network. Two fully-connected layers and relu activation.code

  • Basic convolutional neural network - Simple neural network with 2 convolutional layers, relu activation, maxpooling and fully-connected layer. code

Winners solutions

The winning codes can be found in the notebooks section. Number of the file indicates the postion of the solution in the rank.

Owner

  • Name: Agnieszka Mikołajczyk
  • Login: AgaMiko
  • Kind: user
  • Location: Gdańsk
  • Company: Gdansk University of Technology/ Voicelab.ai

Machine Learning Scientist & Enthusiast🤖 https://twitter.com/AgnMikolajczyk LN: https://www.linkedin.com/in/agnieszkamikolajczyk/

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Name Email Commits
Agnieszka Mikołajczyk a****k@p****l 8
AgaMiko a****g@g****m 6
MarcinKurylo 6****o 2
Agnieszka Mikołajczyk m****n@g****m 1
Kamil-Och 6****h 1
MarvinRac 6****c 1
Michal-crypto 6****o 1
Tai-Min 2****n 1
Committer Domains (Top 20 + Academic)

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