/ml-concepts

📓 Short, atomic notes on concepts in machine learning.

📓 ml-concepts

Short, atomic notes on concepts in machine learning.

Contents

To-do

  • Domain adaption
  • Self-supervised representation learning
  • Gaussian processes
  • Embedding space (how to learn one for e.g., both images and text)
  • spurious correlations (robustness to distribution shifts)