Dive into a comprehensive tutorial on building and deploying a semantic search engine using Hugging Face. Learn the importance of context in Natural Language Processing, construct a semantic search engine from the ground up, and deploy it as an API. Explore backend and frontend examples, evaluation criteria, and integration with Hugging Face API. Gain insights into aspect-based sentiment analysis and keyword creation using transformers. Perfect for data scientists, engineers, and developers looking to enhance their skills in natural language processing and search algorithms. Led by experienced data science professional Hamza Farooq, this 37-minute video covers essential topics from introduction to advanced techniques, providing practical knowledge to elevate your data projects.
Building and Deploying a Semantic Search Engine on Hugging Face
Overview
Syllabus
– Introduction
– The Value of context in NLP Models
– Building a Semantic Search From Scratch-ish
– Semantic Search Engine Backend Example
– Evaluation Criteria
– Semantic Search Engine Frontend Example
– Merging with Hugging Face API
– Summary
– Aspect-based Sentiment Analysis
– Keyword Creation Using Transformers
Taught by
Data Science Dojo
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