Handy Google Colab notebook for Fashion MNIST classification exercise (Lesson 4)

Summary

The website provides a modified Google Colab notebook for the Fashion MNIST classification exercise in Udacity's PyTorch Scholarship Challenge course, which allows users without a GPU to complete the task using Google Colab's free GPU access.

Abstract

The web content introduces a Google Colab notebook tailored for participants of Udacity's "Deep Learning with PyTorch" course, specifically for the Fashion MNIST classification exercise in Lesson 4. This exercise typically requires a GPU for efficient processing, which may not be accessible to all learners. The provided notebook addresses this issue by being optimized for use with Google Colab, which offers free GPU resources. The author, Avinash, has outlined brief steps for users to download and upload the modified notebook to Google Colab, enabling them to execute the exercise without the need for a personal GPU. The notebook includes necessary changes such as installing PyTorch version 0.4, setting the runtime to use a GPU, downloading and unzipping the dataset, and integrating methods from helper.py to avoid the need for uploading additional files. The author encourages users to reach out on Slack for assistance with the notebook.

Opinions

The author believes that using Google Colab is a beneficial alternative for those without access to a GPU.
They express confidence that the modified notebook will help users focus on the exercise rather than the technical setup.
The author is open to providing support, inviting users to message them on Slack if they encounter any issues.
The tone of the content suggests that the author is community-oriented, aiming to facilitate a smoother learning experience for their peers in the course.

Handy Google Colab notebook for Fashion MNIST classification exercise (Lesson 4)

This blog post is for people who are doing Udacity’s PyTorch Scholarship Challenge course: Deep Learning with PyTorch.

In Lesson 4, we get to classify fashion images from MNIST database. This exercise requires access to a GPU. Since not many of us do not have a GPU, a good and free alternative is Google Colab.

So, I created this notebook with all the modifications required so that you can run this on Colab directly. Here are the brief steps:

Download the modified Notebook from this link

Visit Google Colab

You will be prompted with a modal, select Upload

If modal doesn’t appear and instead if it opens a new Notebook, then from menu File > Upload Notebook

Upload the modified notebook

That’s it!

Now you can focus on completing the exercise instead of worrying about how to download the images etc.

If you are interested in knowing changes I have made:

Intsall PyTorch v.0.4

Set the Runtime to GPU, so that GPU is enabled

Download the dataset and unzip it

Add the methods from helper.py so that you don’t need to upload it

Hope this helps! If you have got any issues with running this notebook, then feel free to message me on Slack for any help. My slack username is avinash

All the best for the exercise!