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This must-know guide will provide you with all the information you need to understand vector databases and how they are used in generative AI like LLM. Unlike traditional databases, vector databases excel in identifying similarities between data objects, making them indispensable for tasks like movie recommendations and AI-driven insights. What You'll Learn: 1. Understanding Traditional Databases: Learn how SQL databases organize data in rows and columns, and their limitations with fuzzy queries. 2. Introduction to Vector Databases: Discover how data is represented as multi-dimensional vectors, capturing the essence of text, images, and more. 3. Indexing and Querying: See how vector databases convert data into vectors for efficient storage and retrieval, using algorithms like word embeddings. 4. Real-World Applications: Explore a practical example of recommending movies using vector similarities. 5. Advanced Concepts: Delve into vector storage, indexing algorithms, distance metrics, and query processing engines. 6. Future of AI with RAG: Understand how vector databases enhance Retrieval Augmented Generation (RAG) for contextually relevant AI responses. FOLLOW ME ON: ▶️ Main Channel: /bytemonk Timestamps - 00:00 - Introduction 00:22 - Vector Database 01:01 - Indexing 01:12 - Querying 01:58 - Recommending Movies 03:04 - Core Components 03:07 - Vector Storage 03:31 - Vector Indexing 04:01 - Distance Metrics 04:24 - Query Processing Engine 04:39 - Additional Features 05:20 - RAG LinkedIn: / bytemonk System Design Interview Basics Playlist: ► • System Design Interview Basics AWS Certification: ►AWS Certified Cloud Practioner: • How to Pass AWS Certified Cloud Practition... ►AWS Certified Solution Architect Associate: • How to Pass AWS Certified Solution Archite... ►AWS Certified Solution Architect Professional: • How to Pass AWS Certified Solution Archite... #vector #database #ai