Semantic Search with LLMs

• Get practical experience in semantic search algorithms
• Go beyond theoretical knowledge to apply actionable skills to your projects
• Learn to integrate state-of-the-art NLP frameworks, such as Hugging Face Transformers and vector search databases, for semantic search in real-world applications
• Master complex concepts like quantization through this course designed to make advanced topics accessible and straightforward

Semantic search goes beyond traditional keyword-based queries to understand the context and intent behind a search, providing more relevant and accurate results. This course arms you with the tools and techniques to implement semantic search in diverse applications, from recommendation systems to query-answering systems. As the volume of digital data continues to grow, mastering semantic search will not only make your search algorithms more effective but also provide substantial benefits in data analytics and user engagement.

Using the capabilities of LLMs, this course expands their utility by allowing them to access a vector database full of text and metadata. A vector database essentially maps words into numerical spaces, enabling more nuanced search capabilities that consider context and semantics. The curriculum starts with the basics of transitioning from traditional keyword-based search algorithms to advanced semantic search methods. It then dives into practical exercises that will train you in state-of-the-art techniques, optimizing for speed, cost, and accuracy. Through these hands-on modules, we’ll work through real vector search challenges, allowing you to apply what you've learned in real-world applications.