7 PM – AI/ML – Darin

Today’s Activities:

1. Continued multi-class classification on the MNIST dataset.
2. Learned about data augmentation through the batch_tfms parameter for the dataloader.

Homework:

1. Create a google doc under your homework google drive 
2. Write up your project proposal for training your own AI model detailing:
   – What you will be classifying (has to be multi-class classification!)
   – Where your data comes from (provide a link or methodology of getting the dataset). If you are using an existing dataset, you have to add more images from online means (gather data from outside of kaggle, whether it’s online images, etc)
   – How you will train your AI model (what transformations on the data you will use, and the flow of training)
   You can view the list of transformations here: https://docs.fast.ai/vision.augment.html#aug_transforms

Ensure the google doc is public access and that it is in your homework folder.

Notes:

You can reach me at ddjapri@ayclogic.com.

All class notes can be found here.