Content:
– Embeddings;
– Motivational example: face recognition and clustering;
– Why a standard deep classifier would fail;
– Distance measures / preprocessing / learning;
– Embeddings in general:
– Classifiers;
– Word embeddings;
– Dimensionality reduction;
– Reinforcement learning;
– ...
– Face embeddings and clustering;
– ...
