Implementing and Training a Neural Network with PyTorch
Offered By: Valerio Velardo - The Sound of AI via YouTube
Course Description
Overview
Build and train a feed-forward neural network using PyTorch in this 37-minute tutorial. Develop a classifier to identify digits in the MNIST dataset while learning data management techniques with PyTorch datasets and data loaders. Follow a step-by-step implementation process, starting with PyTorch installation and dataset download. Progress through implementing a data loader, designing a feed-forward network, and creating a training loop. Conclude by training and storing the model, gaining practical experience in neural network development with PyTorch.
Syllabus
Intro
Installing PyTorch with pip
Step-by-step implementation overview
Download datasets
Implementing a data loader
Implementing a feed forward network
Implementing the training loop
Training and storing our model
Coming up next + outro
Taught by
Valerio Velardo - The Sound of AI
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent