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).
As such, it is fitting that our first machine learning example should be dedicated to the classification of handwritten digits. At this point, in the interest of keeping it simple, we will apply a very simple classifier. This simple model will suffice to classify approximately 92% of the test set correctly—the best models currently available reach over 99.75% correct classification.