What is Vector Search? | Vector Databases with Weaviate: Part 2 | Community Webinar
Part 2: Introduction to Vector Search
Vector search is a powerful technique that uses mathematical similarity to identify and retrieve related data efficiently. This Part 2 webinar of the community series with Weaviate offers an introduction to vector search, explaining its core principles, limitations, and how it scales with advanced technologies like vector databases.
What we will cover:
- Understand how similarity is calculated mathematically and its role in data retrieval.
- Explore what basic search lacks when applied at scale.
- Focus on Approximate Nearest Neighbor (ANN) algorithms, …
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Chapters (14)
0:07
Introduction to Vector Search
0:24
Overview of Vector Databases and Vector Search
2:26
Keyword Search Explanation
4:19
Introduction to Vector Search Algorithms (k-NN)
7:11
Implementing Vector Search in Python
11:08
Performance at Scale: k-NN vs. ANN Algorithms
17:15
Weaviate’s Custom HNSW Implementation
19:23
Multimodal and Multilingual Vector Search
22:15
Hybrid Search: Combining Keyword and Vector Search
24:01
Challenges of Scaling Vector Search
28:44
Demo: Implementing Vector Search with Weaviate
35:06
Streamlit Integration for Vector Search
41:26
Advanced Applications and AI Agents
44:09
Audience Q&A and Closing Remarks
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