This project includes all what you need to build a classifier with Pytorch on the Google Colab platform (for using free GPUs)

For detailed information please refert to my Youtube channel, all these notebooks and more are explained in the Pytorch Series in the follwing link:'https://www.youtube.com/playlist?list=PLy7lW2fw6onAknMhacnBXNgLUROWjnV1Z'

The current videos are:

1. Everything you need to Build a classifier with Pytorch: #1 Get started with Google Colab: https://youtu.be/_rtueYEJXtI
2. Everything you need to Build a classifier with Pytorch:#2 Installing/ Importing the needed libraries: https://youtu.be/tkPryh36EtQ
3. #3 Uploading data to Google Colab (local files, from gdrive, Github & Dropbox): https://youtu.be/SkV82klGbVw
4. #4: Image Transforms, ImageFolder, DataLoader, Sampler, use data from Google Drive: https://youtu.be/5rW_PZI4B2I

Some other videos that might be useful but are not part of the Pytorch series are:

1. Saving/ Loading model checkpoint in Pytorch (example 1: Vgg16): https://youtu.be/7leJqHk6Dn0
2. Saving/ Loading checkpoints in Pytorch (Example 2: Resnet 18): https://youtu.be/07obsF0bOUA
3. Learning Rate Schedulers (Examples: StepLR, Multi Step LR, Exponential LR) / Pytorch: https://youtu.be/Ng0MymNz6l0
4. How to participate in Kaggle Competitions & deal with Kaggle Kernels (Oxford 102 Flowers Pytorch): https://youtu.be/IIQjYxo1-zQ
5. How to open case for getting AWS Promotional Credits: https://youtu.be/waDOnSsZRzs
6. Finally, I made it! :) Nano degree in Deep Learning! Pytorch: https://youtu.be/65hFGnoCaOc