jiangyangzhou/mnist_tutorial

A tutorial for mnist hand writen digit classification using sklearn, pytorch and keras.

mnist_tutorial

A tutorial for mnist hand writen digit classification using sklearn, pytorch and keras.

Code structure

• numpy_matplotlib_sklearn.ipynb: for numpy, matplotlib and sklearn.
• pytorch.ipynb: for pytorch.
• keras.ipynb: for keras.
• Reference solution: (not published yet)
  • numpy_matplotlib_sklearn_solution.ipynb
  • pytorch_solution.ipynb
  • keras_solution.ipynb

Requirements

Code tested on following environments, other version should also work:

• linux system (ubuntu 16.04)
• python 3.6.3
• numpy 1.13.3
• matplotlib 2.1.0
• sklearn 0.19.1
• pytorch 0.4.1
• keras 2.1.2
• tensorflow

For students from SJTU

Please read HEAR.

For Homework readme

I finished [numpy_matplotlib_sklearn_solution.ipynb] and [pytorch_solution.ipynb]
Because I failed to fetch mnist data with sklear API, I use tensorflow API to load mnist data.

• In sklearn part,
  LogisticRegression got test score: 92.57%
  BernoulliNB got test score: 84.13%
  LinearSVC got test score: 91.80%
  SVC got test score: 94.46% (It is too slow.......)

• In pytorch part,
  I designed a simple convolution neural network based on Vgg Net.
  It achieved 99.38% score on test set.
  Cheers!
  Convolution neural network is very powerful, just one epoch, it achieved remarkable precision.