The MNIST (Mixed National Institute of Standards and Technology) handwritten digits dataset is one of the most researched datasets in image processing and machine learning, and has played an important role in the development of artificial neural networks (now generally referred to as deep learning).
In this project, we are building blocks and methods associated with convolutional neural network (CNN). The performance of this model is already relatively good, with just over 99% correct after as little as 5 epocs,1 which are 5,000 steps with mini-batches of size 50.
For a list of models that have been used over the years with this dataset, and some ideas on how to further improve this result, take a look at http://yann.lecun.com/exdb/mnist/.