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AI Engineering / Working with LLMsEmbeddings & Vector Databases

12 items

1

Embedding Dimensionality

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2

How Embeddings Are Generated

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3

Euclidean and Dot Product

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4

What Embeddings Are

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5

Nearest Neighbor Search (KNN)

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6

Cosine Similarity

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7

Semantic Similarity Intuition

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8

Vector DB vs Traditional DB

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9

What a Vector Database Is

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10

Approximate Nearest Neighbor (ANN)

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11

Vector Indexing (HNSW, IVF)

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12

Text vs Multimodal Embeddings

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Vector Indexing (HNSW, IVF)

HNSW and IVF are index structures that accelerate approximate similarity search.

Question

What are HNSW and IVF vector indexing methods?

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← PreviousApproximate Nearest Neighbor (ANN)Next →Text vs Multimodal Embeddings
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