Four Generations of Semantic Search: From TF‑IDF to Transformer Fine‑Tuning
This tutorial walks through building semantic search pipelines step‑by‑step, starting with TF‑IDF with handcrafted features, then classical ML ranking, dense embeddings using Sentence‑Transformers, and finally fine‑tuned BERT models. Each stage is implemented in Python on a synthetic art‑critique dataset, illustrating the evolution of retrieval techniques.