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Building a Semantic Search Engine on Hugging Face | Future of Data & AI | Data Science Dojo
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Unlock the power of semantic search with this hands-on tutorial. Learn how to build a semantic search engine from scratch and deploy it as an API on Hugging Face. Perfect for data scientists, engineers, and developers, this tutorial will cover natural language processing techniques and how to implement a search algorithm that understands user intent. By the end of the tutorial, you will:
- Understand the value of context in Natural Language Processing
- Learn how to build a semantic search engine from scratch.
- Deploy your search engine as an API on Hugging Face.
Whether you’re new to the field or an experienced professional, this tutorial is a great opportunity to enhance your skills and take your data projects to the next level.
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About the Speaker:
Hamza Farooq has over a decade of experience in leading Data Science/ Machine Learning teams. His tenure spans over three continents and seven countries across APAC, Middle East and Africa, and North America and multiple industries, namely, Tech, Telecommunications, Finance, and Retail.
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Table of Contents:
00:00 – Introduction
03:14 – The value of context in NLP models
04:17 – Building a semantic search from scratch
11:55 – Semantic search engine backend example
14:00 – Evaluation criteria
17:23 – Semantic search engine frontend example
20:12 – Merging with Hugging Face API
26:35 – Summary
28:45 – Aspect-based sentiment analysis
31:40 – Keyword creation using transformers
#nlptechniques #huggingface #llms #futureofdataandai
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