Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Welcome to the Zero to Mastery Learn PyTorch for Deep Learning course, the second best place to learn PyTorch on the internet (the first being the PyTorch documentation). 00 - PyTorch Fundamentals ...

This repository contains a tutorial on building neural network models using PyTorch, along with comparisons with TensorFlow. It covers the basics of PyTorch, including tensors, operations, autograd, ...

Pytorch_EHR is a codebase enabling fast prototyping of deep learning-based predictive models using electronic health records structured data. Rather than a collection of vertical pipelines ...

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.

Dr. James McCaffrey of Microsoft Research explains how to define a network in installment No. 2 of his four-part series that will present a complete end-to-end production-quality example of ...

You won’t learn anything about generative adversarial networks (GANs) or Transformer-based networks in either course, and the Udacity course is based on PyTorch 0.4.