Learn how to build a digit recognition model from scratch using PyTorch! This beginner-friendly deep learning project walks you through loading the MNIST dataset, creating a neural network, training ...

This project serves as a clean, well-documented example of both training a CNN from scratch and fine-tuning a pre-trained model using PyTorch. It demonstrates best practices in: pytorch-mnist-resnet/ ...

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 ...

Most neural network libraries, including PyTorch, scikit and Keras, have built-in MNIST datasets. However, working with pre-built MNIST datasets has two big problems. First, a pre-built dataset is a ...

A beginner-friendly project to build, train, and evaluate a neural network using PyTorch for classifying handwritten digits from the MNIST dataset. This project is designed as a step-by-step practical ...

Abstract: this research explores the vulnerability of convolutional neural networks (CNNs) to adversarial attacks, with a focus on the Fast Gradient Sign Method (FGSM) as a baseline threat model. The ...

The choice between PyTorch and TensorFlow remains one of the most debated decisions in AI development. Both frameworks have evolved dramatically since their inception, converging in some areas while ...