Vector Databases Deep Dive

سرفصل های دوره

Mastering Vector Databases: Fundamental Concepts to Advanced Applications in AI and Big Data

1 - Introduction

1 - Introduction to the Course

2 - Course Structure

2 - Introduction to Vector Databases

3 - Introduction to Vector Databases

4 - Key Principles of Vector Databases

5 - Why are Vector Databases all the rage

6 - How Vector Databases Differ from Traditional Databases

7 - Advantages Challenges of Vector Databases

3 - Vector Database Core Concepts

8 - Introduction to Vectors

9 - Real World Illustration on Vectors

10 - Vectors and their roles in databases

11 - Introduction to Embeddings

12 - Embeddings Illustrations Fraud Detection Example

13 - Introduction to Dimensionality and HighDimension Spaces

14 - Challenges with HighDimensional Data

15 - Distance Metrics and Similarity

16 - Euclidean Distance

17 - Manhattan Distance

18 - Cosine Distance

19 - Jaccard Similarity

4 - Understanding Search Similariity

20 - The Importance of Search Similarity

21 - KNearest Neighbors

22 - Approximate Nearest Neighbors

23 - KNN vs ANN

5 - Indexing and Querying

24 - Indexing Strategies

25 - Flat Index

26 - Flat Index Imagined Real World Illustration

27 - Inverted File Index

28 - Inverted File Index Imagined Real World Illustration

29 - Approximate Nearest Neighbors Oh Yeah ANNOY

30 - ANNOY Imagined Real World Illustration

31 - Product Quantization

32 - Product Quantization Imagined Real World Illustration

33 - Hierarchical Navigable Small World HNSW

34 - HNSW Imagined Real World Illustration

35 - Selecting the right index

6 - Working with Vector Databases

36 - Vector Database or Vector Store

37 - Pinecone

38 - Qdrant

39 - Milvus

40 - Weaviate

7 - Demo

41 - Pinecone Demo

8 - The Future of Vector Daabases

43 - The Future of Vector Databases

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تولید کننده: Udemy