Introduction to AI-Native Vector Databases

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Zain Hasan

2:47:38

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01 - Introduction

01 - Learning AI-native vector databases.mp4

00:50

02 - What you should know.mp4

00:45

03 - The superpower of vector databases.mp4

02:07

02 - 1. Data What Data Do Vector Databases Store and How Is It Stored

01 - Structured versus unstructured data.mp4

02:49

02 - Human-understandable versus machine-understandable data.mp4

03:35

03 - Drawing out and visualizing vector representations of data.mp4

03:40

04 - Introduce the concept of distance between two vectors.mp4

02:20

05 - Challenge Working with vectors.mp4

00:51

06 - Solution Working with vectors.mp4

16:16

03 - 2. Natural Querying How Do You Search for Data in a Vector Database

01 - Frame the query as a question or search.mp4

01:56

02 - Generate the question in machine-understandable language.mp4

01:22

03 - Adding data to a vector database.mp4

09:48

04 - Performing semantic searches using Weaviate.mp4

13:36

05 - Challenge Vector search with Weaviate.mp4

00:49

06 - Solution Vector Search with Weaviate.mp4

11:05

04 - 3. Machine Learning Vectors How Does a Vector Database Understand Your Data

01 - Machine learning models and object classification.mp4

02:02

02 - Translating data from human to machine-understandable.mp4

02:11

03 - ML models and vector embeddings.mp4

15:52

04 - Challenge Search with images and text.mp4

00:51

05 - Solution Search with images and text.mp4

14:28

05 - 4. Scalability What Does a Vector Database Need to Do

01 - Scalability When to use a vector DB.mp4

02:43

02 - Ways to measure performance of a vector DB.mp4

02:26

03 - CRUD operations in vector DBs.mp4

09:58

04 - Challenge CRUD and performance.mp4

00:55

05 - Solution CRUD and performance.mp4

08:49

06 - 5. Demonstrate Vector DBs and Use Cases

01 - Vector DB1 E-commerce RecSys.mp4

09:15

02 - Vector DB2 Hybrid search.mp4

09:06

03 - Vector DB3 Retrieval augmented generation.mp4

09:06

04 - Challenge Vector DBs.mp4

01:00

05 - Solution Vector DBs.mp4

06:12

07 - Conclusion

01 - Continue your AI-native vector databases learning journey.mp4

00:55

Description

The primary purpose of vector databases is to provide fast and accurate similarity search or nearest neighbor search capabilities. The integration of AI techniques in vector databases enhances their capabilities, improves search accuracy, optimizes performance, and enables more intelligent and efficient management of high-dimensional data. In this course, Zain Hasan introduces this foundational technology—which is already being used in industries like ecommerce, social media, and more. Zain covers everything from foundational concepts around AI-first vector databases to hands-on coding labs for question answering using LLMs.

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Artificial Intelligence

Database Programming

Zain Hasan

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Linkedin Learning

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.