Udemy - Introduction to Qdrant (Vector Database) Using Python

磁力链接/BT种子名称

Udemy - Introduction to Qdrant (Vector Database) Using Python

磁力链接/BT种子简介

种子哈希：fdf485c8318768bcc412c270625f36c9358100ff
文件大小：787.71M
已经下载：102次
下载速度：极快
收录时间：2024-12-31
最近下载：2025-01-01

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文件列表

  • 2. Qdrant - Basics/1. Introduction and Installation.mp4 69.9 MB
  • 1. Introduction/3. Components of a Vector Databases.mp4 57.6 MB
  • 2. Qdrant - Basics/11. Vector similarity search in Qdrant - Part 2.mp4 48.6 MB
  • 1. Introduction/6. Vector Similarity Metrics.mp4 47.9 MB
  • 1. Introduction/4. Vector Embeddings.mp4 47.6 MB
  • 3. Qdrant - Advanced/10. Configuring Qdrant.mp4 46.5 MB
  • 4. Qdrant - Examples (Optional)/2. Qdrant + OpenAI.mp4 44.3 MB
  • 4. Qdrant - Examples (Optional)/1. Qdrant + Tensorflow.mp4 43.3 MB
  • 2. Qdrant - Basics/6. Points.mp4 42.8 MB
  • 2. Qdrant - Basics/9. Vector Similarity Search in Qdrant - Part 1.mp4 40.4 MB
  • 4. Qdrant - Examples (Optional)/3. Qdrant + LangChain.mp4 36.7 MB
  • 2. Qdrant - Basics/4. Collections.mp4 31.0 MB
  • 1. Introduction/2. Vector Databases.mp4 30.2 MB
  • 3. Qdrant - Advanced/7. Vector Quantization - Part 2.mp4 29.7 MB
  • 3. Qdrant - Advanced/5. Vector Quantization - Part 1.mp4 27.0 MB
  • 3. Qdrant - Advanced/11. Optimizers.mp4 27.0 MB
  • 3. Qdrant - Advanced/3. Vector Index.mp4 25.8 MB
  • 3. Qdrant - Advanced/1. Payload Indexes.mp4 25.5 MB
  • 1. Introduction/1. Introduction.mp4 22.8 MB
  • 3. Qdrant - Advanced/12. Qdrant - Async Python Client.mp4 22.7 MB
  • 2. Qdrant - Basics/8. Loading a Dataset into Qdrant.mp4 18.7 MB
  • 2. Qdrant - Basics/2. Qdrant Storage Model.mp4 14.7 MB
  • 5. Conclusion/1. Conclusion.mp4 12.8 MB
  • 3. Qdrant - Advanced/9. Snapshots.mp4 12.4 MB
  • 2. Qdrant - Basics/9.1 3.search.ipynb 140.4 kB
  • 2. Qdrant - Basics/6.1 2.Points.ipynb 11.7 kB
  • 4. Qdrant - Examples (Optional)/2.1 8.openai_example.ipynb 10.1 kB
  • 4. Qdrant - Examples (Optional)/1.1 7.tf_example.ipynb 8.9 kB
  • 2. Qdrant - Basics/4.1 1.collections.ipynb 5.4 kB
  • 3. Qdrant - Advanced/5.1 5.quantization.ipynb 4.8 kB
  • 4. Qdrant - Examples (Optional)/3.1 9.langchain_example.ipynb 4.8 kB
  • 3. Qdrant - Advanced/1.1 4.Indexes.ipynb 4.5 kB
  • 3. Qdrant - Advanced/9.1 6.snapshots.ipynb 3.9 kB
  • 4. Qdrant - Examples (Optional)/3.2 nobel_physics_2023.txt 2.3 kB
  • 3. Qdrant - Advanced/12.1 async_example.py 546 Bytes
  • 2. Qdrant - Basics/1.1 docker-compose.yaml 262 Bytes
  • 1. Introduction/5. Vector Embeddings.html 133 Bytes
  • 1. Introduction/7. Vector Similarity.html 133 Bytes
  • 2. Qdrant - Basics/3. Qdrant Storage Model.html 133 Bytes
  • 2. Qdrant - Basics/5. Collections.html 133 Bytes
  • 2. Qdrant - Basics/7. Points.html 133 Bytes
  • 2. Qdrant - Basics/10. Similarity Search - Part 1.html 133 Bytes
  • 2. Qdrant - Basics/12. Similarity Search - Part 2.html 133 Bytes
  • 3. Qdrant - Advanced/2. Payload Indexes.html 133 Bytes
  • 3. Qdrant - Advanced/4. Indexing the Vectors.html 133 Bytes
  • 3. Qdrant - Advanced/6. Quantization - Part 1.html 133 Bytes
  • 3. Qdrant - Advanced/8. Vector Quantization - Part 2.html 133 Bytes

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