吴正龙’s Bookmarks

Visual walkthrough of how various gradient descent methods work. Assumes basic familiarity of why and how gradient descent is used in machine learning.

Overview of different types of transfer learning techniques, and how they can be used to transfer knowledge to a different task, language or domain.

A whirlwind tour of PyTorch's internals, covering tensors, autograd, and the overall structure of the project. Meant for aspiring OSS contributors.

BERT was a model that broke several records for how well models could handle language-based tasks.

Overview of transfer learning and discussion of practical applications and methods.

Backpropagation is a leaky abstraction. It is a credit assignment scheme with non-trivial consequences. Ignoring how it works under the hood because "TensorFlow automagically makes my networks learn" means you won't be ready to wrestle with the dangers it presents.