Скачать с ютуб Build Semantic-Search with Elastic search and BERT vector embeddings. ( From scratch ) в хорошем качестве

Build Semantic-Search with Elastic search and BERT vector embeddings. ( From scratch )

project code: https://github.com/abidsaudagar/seman... Welcome to my comprehensive coding tutorial where we'll discuss the process of creating a powerful semantic search engine from scratch! In this video, we'll combine Elasticsearch, SBERT machine learning models, and Streamlit to build a robust search application that understands the meaning behind our queries. What we'll discuss: Setting Up Elasticsearch: We'll start by setting up Elasticsearch, a highly scalable and flexible search engine, as the backbone of our semantic search system. We'll learn how to index your data effectively for efficient searching. SBERT Embeddings: Dive into the world of SBERT (Sentence-BERT) and discover how to use pre-trained language models to transform text into meaningful numerical representations that capture semantic information. Semantic Search Algorithms: Learn how to implement semantic search algorithms that can find contextually relevant results, going beyond traditional keyword-based searches. Streamlit User Interface: We'll create an interactive and user-friendly front-end using Streamlit, allowing you to search and explore your data effortlessly. By the end of this tutorial, you'll have the skills to build your own semantic search engine and customize it to suit your specific needs. Whether you're a developer looking to enhance search capabilities or a data enthusiast interested in understanding semantic search, this video is your gateway to creating intelligent and context-aware search solutions. Don't miss out on this in-depth coding tutorial! Join us as we unlock the potential of semantic search using Elasticsearch, SBERT, and Streamlit. Subscribe, like, and share to stay updated with the latest tutorials on building advanced AI-powered applications. Let's start searching smarter today! 0:00 - Intro 0:28 - How end product will look like! 1:07 - Architecture 3:37 - Setup Elastic Search server 4:43 - Connecting to Elastic Search using Python API 9:14 - Data Prepration 12:21 - Vector Conversion using S BERT model 16:50 - Creating index in Elastic Search for KNN search 23:27 - Data ingestion in Elastic Search index. 26:58 - Writing search function to retrieve the data from Elastic Search! 30:57 - Streamlit UI 35:09 - Yayy!! Using Final Search UI. 38:25 - Thank You LEARN PYTHON STEP BY STEP : 1. Learn Python in 15 minutes :    • Learn Python in 15 minutes! (in Hindi)   2. Functions in Python :    • Functions in python for beginners (in...   YOU CAN FIND ME HERE AS WELL : My Instagram:   / abidsaudagar   My LinkedIn:   / abidsaudagar