Master Vector Databases --> [ DevCourseWeb ]

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Torrent File Content (51 files)

[ DevCourseWeb.com ] Udemy - Master Vector Databases
Get Bonus Downloads Here.url -

182 bytes

~Get Your Files Here !
1. Introduction/1. Introduction to Vector Database.mp4 -

86.29 MB

1. Introduction/2. Vectors and Embeddings.mp4 -

40.74 MB

1. Introduction/3. Explain vector database like I'm 5.mp4 -

29.9 MB

1. Introduction/4. How vector database store data.mp4 -

32.08 MB

1. Introduction/5. How do vector database works.mp4 -

26.82 MB

1. Introduction/6. Vectors in 2D.mp4 -

36.97 MB

2. The power of embeddings/1. Create embeddings using OpenAI.mp4 -

92.43 MB

2. The power of embeddings/1.1 VD_Vector_Embedding_OpenAI.ipynb -

47.51 KB

2. The power of embeddings/2. Sentence Embedding Models.html -

3.52 KB

3. Using SQLite as vector storage/1. Setup and basic operations.mp4 -

55.33 MB

3. Using SQLite as vector storage/2. Creating, storing and retrieving vector data.mp4 -

142.76 MB

3. Using SQLite as vector storage/2.1 VD_SQLite_Vector_search.ipynb -

16.83 KB

3. Using SQLite as vector storage/3. Finding nearest vector.mp4 -

48.33 MB

3. Using SQLite as vector storage/4. Vector search using sqlite-vss extension.mp4 -

149.17 MB

3. Using SQLite as vector storage/4.1 VD_SQLite_VSS.ipynb -

12.04 KB

4. ChromaDB/1. Introduction to ChromaDB.mp4 -

125.39 MB

4. ChromaDB/2. Revolutionizing the Data access with Vector Database.html -

5.21 KB

4. ChromaDB/3. Methods on collections.mp4 -

60.64 MB

4. ChromaDB/3.1 Vector_Database_ChromaDB.ipynb -

2.48 KB

4. ChromaDB/4. Storing The Matrix collections.mp4 -

103.87 MB

4. ChromaDB/4.1 Vector_Database_ChromaDB__The_Matrix_.ipynb -

25.25 KB

4. ChromaDB/5. Adding document associated embeddings.mp4 -

95.98 MB

4. ChromaDB/6. Query data with 'where' filter.mp4 -

96.01 MB

4. ChromaDB/7. ChromaDB + Langchain - QA on multiple documents - Part 1.mp4 -

133.28 MB

4. ChromaDB/7.1 VD_ChromaDB_+_Langchain_QA_Multiple_documents.ipynb -

27.23 KB

4. ChromaDB/8. ChromaDB + Langchain - QA on multiple documents - Part 2.mp4 -

92.11 MB

5. Facebook AI Similarity Search (FAISS)/1. Introduction to FAISS.mp4 -

127.59 MB

5. Facebook AI Similarity Search (FAISS)/2. Using similarity search for nearest neighbours.mp4 -

66.99 MB

6. Pinecone/1. Introduction to Pinecone.mp4 -

113.01 MB

6. Pinecone/10. Vector IDs must be string.mp4 -

51.07 MB

6. Pinecone/11. Sentence transformer embeddings.mp4 -

85.82 MB

6. Pinecone/12. Semantic search with metadata filtering - news articles.mp4 -

252.75 MB

6. Pinecone/2. Setup account, create an index, dashboard review.mp4 -

96.99 MB

6. Pinecone/3. Understanding index creation configuration.mp4 -

82.86 MB

6. Pinecone/4. Index management.mp4 -

114.89 MB

6. Pinecone/5. Insert vector data to an index.mp4 -

104.72 MB

6. Pinecone/6. Query vector data.mp4 -

94.27 MB

6. Pinecone/7. Upsert vector data in batches.mp4 -

100.32 MB

6. Pinecone/8. Upsert batches in parallel.mp4 -

17.71 MB

6. Pinecone/9. Upsert with metadata.html -

381 bytes

7. Qdrant/1. Introduction to Qdrant vector database.mp4 -

82.22 MB

7. Qdrant/2. Connect with APIs.mp4 -

59.84 MB

7. Qdrant/3. Create a qdrant python client.mp4 -

37 MB

7. Qdrant/4. Create a collection.mp4 -

53.32 MB

7. Qdrant/5. Create a vector store.mp4 -

45.25 MB

7. Qdrant/6. Add document to vector store on the cloud.mp4 -

118.7 MB

7. Qdrant/7. Query the document.mp4 -

85.96 MB

7. Qdrant/8. Create a streamlit QA app.html -

940 bytes

8. Congratulations and Thank You!/1. Your feedback is very valuable!.html -

690 bytes

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