7 PM – AI/ML – Darin

Today’s Activities:

1. Continued on the first project: dog and cat classification
2. Learnt about the labelling function, and commenced training with a GPU for classification

Homework:

Run training again like we did in class, but this time using 3 different AI backbones (replacing the ‘resnet34’ under the vision_learner function call).

Look up the different AI backbones from these links (just try around like resnet50, resnet18, or even ulearner etc):

https://docs.pytorch.org/vision/stable/models.html#initializing-pre-trained-models
https://docs.fast.ai/vision.learner.html#vision_learner

Then make your dataset have at least 10 images (I recommend looking for pictures of cats that look like dogs, and dogs that look like cats), and test these images with your newly trained models.

Write in the same file Jan12_CatVSDog.ipynb as to which AI backbone you think is better in a text box. Upload this file to google drive when you are done.

Notes:

You can reach me at ddjapri@ayclogic.com.

All class notes can be found here.