Concise Lecture Notes - Lesson 6 | Fastai v3 (2019)

These notes were typed out by me while watching the lecture, for a quick revision later on. To be able to fully understand them, they should be used alongside the jupyter notebooks that are available here:

Some other very important links:




Batch Normalization

In what proportion would you use dropout vs. other regularization errors, like, weight decay, L2 norms, etc.?

Data Augmentation

Convolutional Neural Network

Ethics in Data Science

“We know that these are not humans. We know that they are animals, because we read the news. We read the internet.”

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