Fashion Image Classification using CNNs in Pytorch

Offered By
Coursera Project Network
In this Guided Project, you will:

Learn How to use Pytorch to create Neural Network Models.

Learn How to build and train Convolutional Neural Networks in Pytorch.

Clock2 hours
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this 1-hour long project-based course, you will learn how to create Neural Networks in the Deep Learning Framework PyTorch. We will creating a Convolutional Neural Network for a 10 Class Image Classification problem which can be extended to more classes. We will start off by looking at how perform data preparation and Augmentation in Pytorch. We will be building a Neural Network in Pytorch. We will add the Convolutional Layers as well as Linear Layers. We will then look at how to add optimizer and train the model. Finally, we will test and evaluate our model on test data. The project will get you introduced with Pytorch. You will in the end understand how the framework works and get you started with building Neural Networks in Pytorch. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

Convolutional Neural NetworkDeep Learningpytorchimage classification

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Introduction to the Task, Google Colab, CNNs, Pytorch

  2. Setting up Data preparation & Augmentation using Transforms

  3. Importing & Loading Data

  4. Building the Convolutional Neural Network

  5. Training the Neural Network Model

  6. Testing and Evaluating the Model

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.