ACM AI | Advanced Track W23 #6: PyTorch CIFAR-10 Guided Project

Are you interested in learning more about using PyTorch for image classification tasks? Join us for our guided project on working with the CIFAR-10 dataset using PyTorch. This project is part of the Advanced Track sessions offered by ACM AI.

Project Overview

In this guided project, you will learn how to build a convolutional neural network (CNN) using PyTorch to classify images from the CIFAR-10 dataset. The CIFAR-10 dataset consists of 60,000 32×32 color images in 10 classes, with 6,000 images per class. By the end of the project, you will have a trained model that can accurately classify images from the CIFAR-10 dataset.

Prerequisites

To participate in this guided project, you should have a basic understanding of Python and deep learning concepts. Familiarity with PyTorch and image classification tasks will be beneficial, but not required.

How to Join

This guided project will be held on ACM AI’s online platform. To join, simply RSVP for the event and you will receive a link to access the project materials and live session. Make sure to have PyTorch installed on your machine before the session begins.

Get Started with PyTorch

If you are new to PyTorch, we recommend checking out the official PyTorch documentation and tutorials to get acquainted with the framework. You can also explore open-source projects and resources available online to enhance your PyTorch skills.

Mark Your Calendar

Don’t miss out on this opportunity to learn and collaborate with fellow AI enthusiasts. Mark your calendar for the ACM AI | Advanced Track W23 #6: PyTorch CIFAR-10 Guided Project and get ready to dive into the world of deep learning with PyTorch.