~~~~~~~~~~~~~read me~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The goal of this lab is :
    - Evaluate your understanding of the course
    - Try and make a comparison of different machine learning methods
    
This study is based on the http://yann.lecun.com/exdb/mnist/MNist dataset</A>. It is a handwritten digits dataset with a training set of 60000 samples and a test set of 10000 samples. It is a subset of a larger set available from NIST. The digits have been size-normalized and centered in a fixed-size image.

File Information: 

1) Evalation_Mnist.ipynb  : This notebook is an evaluation on Mnist Dataset, which contains binary images of handwritten digits. I have build three classification model to train the dataset, i.e: CNN, Neural Network using PyTorch, and Linear Support vector classifier to check which one gives the best accuracy. You can edit and manipulate the code as you wish.

2) mnist.py: MNist dataset is proposed in keras.datasets toolbox, you can use this code to load the dataset or use the function mnist_load_data provided in mnist.py file

Suggestions are highly appreciated!