Lessons
1
What is a representation? Geometry of meaning
2
Word embeddings: the skip-gram model
3
Word2Vec training: negative sampling
4
Cosine similarity and vector arithmetic
5
Contrastive loss: learning by comparison
6
Triplet loss and metric learning
7
SimCLR and modern contrastive learning