AWS Bedrock RAG Demo in Python (Embeddings + Similarity Search) | AIF-C01 Ep 6 скачать в хорошем качестве

AWS Bedrock RAG Demo in Python (Embeddings + Similarity Search) | AIF-C01 Ep 6

AWS Certified AI Practitioner (AIF-C01) – Episode 6: AWS Bedrock RAG Demo (Python) Timestamps: 0:00 Demo Prerequisites 3:20 LLM Models Used 8:00 RAG Code Explanation(Python) 18:00 RAG in Action!! 21:54 Exam Summary & Questions In this hands-on episode, we build a Mini-RAG pipeline end-to-end using Amazon Bedrock: ✅ Create embeddings with Titan Text Embeddings v2 ✅ Perform similarity search (nearest match using cosine similarity) ✅ Use Llama 3 Instruct to generate a grounded answer from retrieved context ✅ Understand exactly how RAG reduces hallucinations What you’ll learn How embeddings represent “meaning” as vectors How similarity search retrieves the most relevant chunks How RAG works: Retrieve → Ground → Generate How to force the model to answer ONLY from context (grounding) Models used Embeddings: Amazon Titan Text Embeddings v2 LLM: Meta Llama 3 Instruct (Bedrock) Link to Code - https://github.com/aakash1999/AWSBedr... #aws #awscertification #awsaiPractitioner #aifc01 #examprep #amazonbedrock #rag #embeddings #semanticsearch #similaritysearch #machinelearning #generativeai #llama3 #python #cloudcomputing