| 1 -Python Anaconda Install.mp4 | 88.8 MB | ||
| 2 -1. Document Loaders, Chunking, Embeddings, and Vector Search.mp4 | 116.1 MB | ||
| 3 -Understanding RAG Queries, Retrievers, Knowledge Base & Python Document Loading.mp4 | 122.3 MB | ||
| 4 -3. Chunking Large Documents and Creating Embeddings for LLMs.mp4 | 159.1 MB | ||
| 5 -4.Vector Databases, Similarity Search, and Retrievers in RAG with Gemini.mp4 | 215.7 MB | ||
| 5 -RAG_code.py | 1.8 KB | ||
| 5 -rag_doc.pdf | 453.3 KB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B |
Master RAG for AI + DevOps
https://WebToolTip.com
Published 8/2025
Created by Vimal Daga
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 5 Lectures ( 1h 28m ) | Size: 702 MB
Build AI that Searches, Reads & Responds with Your Data
What you'll learn
Understand Retrieval Augmented Generation (RAG) architecture.
Implement document loading and preprocessing for AI models.
Apply chunking techniques to handle large-scale documents.
Work with vector databases for similarity search and retrieval.
Using RAG to enhance LLM performance with domain-specific data.
Integrate retrievers to connect user queries with relevant context.
Requirements
No prior knowledge of RAG or LLMs needed we’ll teach you everything step by step.
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Udemy - LoadRunner Essentials - Master Performance Testing and Analysis Posted by
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