Description
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Dive deep into the architecture behind LLMs by exploring attention mechanisms, transformers, and embeddings. This course will take you through key concepts in AI, how transformers generate language, and the role of embeddings in semantic search. You’ll also learn practical techniques for training transformer models and integrating vector databases to enhance search capabilities.
What you'll learn
- Understand the fundamentals of attention mechanisms and their role in transformers.
- Explore how neural networks and transformers generate language.
- Learn about embeddings and their applications in generating text and semantic search.
- Gain insights into how to train and optimize transformer models.
- Discover the importance of vector databases in improving search performance.
- Master the use of semantic search to enhance retrieval and query understanding.
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