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Learn to develop multilingual sentence transformers with James Briggs in under an hour. Understand how multilingual models work, the datasets to use, and how to apply pretrained models.
Explore the merger of vision and language in machine learning with Vision Transformers (ViT). Learn to implement ViT using Python and Hugging Face for image classification in under an hour.
Learn to enhance YouTube search using OpenAI's Whisper, transformers, and vector search in this short, project-based offering by James Briggs.
Learn to fine-tune classification models using vector search with less than 100 labeled examples in under an hour with James Briggs.
Learn to evaluate search and recommender systems using popular offline metrics like Recall@K, MRR, MAP@K, and NDCG@K with Python in less than an hour with James Briggs.
Explore the subdomain of Natural Language Processing (NLP) with a focus on Question-Answering (QA) in less than an hour. Offered by James Briggs, this study delves into QA tools, their benefits, and applications.
Learn to fine-tune bi-encoder models for semantic search using GenQ, a method that generates synthetic training data. Offered by James Briggs, it takes less than an hour.
Learn to build a Q&A AI using Python in less than an hour with James Briggs. Master open-domain question-answering (ODQA) to retrieve information in a natural, human-like way.
Explore semantic search and question-answering in NLP with James Briggs. Learn about different QA forms, their components, and applications in under an hour.
Learn to fine-tune high-quality sentence transformers using multiple negatives ranking (MNR) loss in under an hour with James Briggs.
Learn to fine-tune sentence transformers using NLI softmax loss with James Briggs. This under 1-hour material covers training, preprocessing, and results.
James Briggs offers a concise guide to understanding and implementing HNSW for vector similarity search using Faiss in Python, in under an hour.
Learn to apply fast and accurate filters to vector searches on massive datasets with James Briggs' under 1-hour material, including Pinecone's solution to filtering.
Learn the traditional approach to Locality Sensitive Hashing (LSH) with James Briggs. This under 1-hour material covers shingling, MinHashing, and banded LSH function.
Learn to train and test an Italian BERT model from scratch with James Briggs. This under 1-hour tutorial covers DataLoader, RoBERTa config, training loop, and testing.
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