Pytorch-MNIST-colab

Implementation of simple model trined on MNIST dataset built in Pytorch farmework using google colab.

Data Overview

MNIST ("Modified National Institute of Standards and Technology") is the de facto “hello world” dataset of computer vision. Since its release in 1999, this classic dataset of handwritten images has served as the basis for benchmarking classification algorithms. As new machine learning techniques emerge, MNIST remains a reliable resource for researchers and learners alike. The MNIST database contains 60,000 training images and 10,000 testing images. Half of the training set and half of the test set were taken from NIST's training dataset, while the other half of the training set and the other half of the test set were taken from NIST's testing dataset.

Model

This is a simple fully connected model with just one hidden layer.

Result

The model acheives accuracy of ~98%

Note: you don't need to install anything to run this model, just open the colab notebook, select the GPU runtime and enjoy.