What you will learn -

• Introduction to Vector Databases and Their Role in Modern AI Applications
• Understanding Text Embeddings and Vector Representations in AI
• Exploring Different Types of Vector Databases and Their Use Cases in Generative AI
• Setting Up Your First Vector Database with Pinecone
• Exploring Alternative Vector Databases
• Unleashing the Power of Text Embeddings
• Best Practices for Text Preprocessing in Embedding Generation
• Unlocking Semantic Search
• Vector Database Indexing Strategies for Optimal Performance in Generative AI Applications
• Building a Simple Question-Answering System Using Embeddings
• Advanced Vector Search Techniques
• Scaling Vector Databases
• Real-time Vector Database Updates and Maintenance for Generative AI
• Implementing Document Retrieval Systems with Vector Search for Generative AI
• Building a Semantic Search Engine Using Vector Databases
• Vector Database Security and Access Control Implementation
• Optimizing Vector Database Performance and Cost Management for Generative AI
• Multi-Modal Embeddings
• Building RAG Applications with Vector Databases and LLMs
• Advanced Vector Database Architectures for Enterprise Applications