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All You Need to Know on Multilingual Sentence Vectors (1 Model, 50+ Languages)
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Classroom Contents
NLP for Semantic Search Course
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- 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
