Completed
Intro to Dense Vectors for NLP and Vision
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
NLP for Semantic Search Course
Automatically move to the next video in the Classroom when playback concludes
- 1 Intro to Dense Vectors for NLP and Vision
- 2 Intro to Sentence Embeddings with Transformers
- 3 Fine-tune Sentence Transformers the OG Way (with NLI Softmax loss)
- 4 Fine-tune High Performance Sentence Transformers (with Multiple Negatives Ranking)
- 5 All You Need to Know on Multilingual Sentence Vectors (1 Model, 50+ Languages)
- 6 Today Unsupervised Sentence Transformers, Tomorrow Skynet (how TSDAE works)
- 7 Evaluation Measures for Search and Recommender Systems
- 8 Making The Most of Data: Augmented SBERT
- 9 AugSBERT: Domain Transfer for Sentence Transformers
- 10 Question-Answering in NLP (Extractive QA and Abstractive QA)
- 11 How to build a Q&A AI in Python (Open-domain Question-Answering)
- 12 How to build a Q&A Reader Model in Python (Open-domain QA)
- 13 Train Sentence Transformers by Generating Queries (GenQ)
- 14 Is GPL the Future of Sentence Transformers? | Generative Pseudo-Labeling Deep Dive
