Abstract: In the ongoing era of noisy intermediate scaled quantum computers, one of the possible applications to search for an advantage of quantum computing is machine learning. Here we report about ...

This project involves the classification of handwritten digits using three different classifiers: Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), and Decision Trees. The goal is to ...

[Click on image for larger view.] Figure 1: CNN for MNIST Data Using PyTorch Demo Run After training, the demo program computes the classification accuracy of the model on the training data (96.60 ...

Dr. James McCaffrey of Microsoft Research details the "Hello World" of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset. The "Hello World" of image ...

Implementation of convolution neural network on the MNIST data set for digit recognition using Python The CNN was implemented in Python, based on the provided C# code. The implementation was done on ...