Master Vector Databases

Files Included :

1 Introduction to Vector Database.mp4 (86.29 MB)
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2 Vectors and Embeddings.mp4 (40.74 MB)
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3 Explain vector database like I'm 5.mp4 (29.9 MB)
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4 How vector database store data.mp4 (32.08 MB)
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5 How do vector database works.mp4 (26.82 MB)
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6 Vectors in 2D.mp4 (36.97 MB)
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1 Create embeddings using OpenAI.mp4 (92.43 MB)
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1 Setup and basic operations.mp4 (55.33 MB)
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2 Creating, storing and retrieving vector data.mp4 (142.76 MB)
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3 Finding nearest vector.mp4 (48.33 MB)
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4 Vector search using sqlite-vss extension.mp4 (149.17 MB)
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1 Introduction to ChromaDB.mp4 (125.39 MB)
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3 Methods on collections.mp4 (60.64 MB)
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4 Storing The Matrix collections.mp4 (103.87 MB)
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5 Adding document associated embeddings.mp4 (95.98 MB)
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6 Query data with 'where' filter.mp4 (96.01 MB)
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7 ChromaDB + Langchain - QA on multiple documents - Part 1.mp4 (133.28 MB)
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8 ChromaDB + Langchain - QA on multiple documents - Part 2.mp4 (92.11 MB)
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1 Introduction to FAISS.mp4 (127.59 MB)
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2 Using similarity search for nearest neighbours.mp4 (66.99 MB)
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1 Introduction to Pinecone.mp4 (113.01 MB)
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10 Vector IDs must be string.mp4 (51.07 MB)
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11 Sentence transformer embeddings.mp4 (85.82 MB)
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12 Semantic search with metadata filtering - news articles.mp4 (252.75 MB)
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2 Setup account, create an index, dashboard review.mp4 (96.99 MB)
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3 Understanding index creation configuration.mp4 (82.86 MB)
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4 Index management.mp4 (114.89 MB)
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5 Insert vector data to an index.mp4 (104.72 MB)
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6 Query vector data.mp4 (94.27 MB)
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7 Upsert vector data in batches.mp4 (100.32 MB)
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8 Upsert batches in parallel.mp4 (17.71 MB)
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1 Introduction to Qdrant vector database.mp4 (82.22 MB)
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2 Connect with APIs.mp4 (59.84 MB)
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3 Create a qdrant python client.mp4 (37 MB)
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4 Create a collection.mp4 (53.32 MB)
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5 Create a vector store.mp4 (45.25 MB)
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6 Add document to vector store on the cloud.mp4 (118.7 MB)
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7 Query the document.mp4 (85.96 MB)
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