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Language:
English
Total Size:
1.8 GB
Info Hash:
44193ED76A9C65A213E0B4615E756ACFE93961DB
Added By:
Added:
May 29, 2025, 6:51 a.m.
Stats:
|
(Last updated: Nov. 24, 2025, 4:13 p.m.)
| File | Size |
|---|---|
| Get Bonus Downloads Here.url | 180 bytes |
| 001. Part 1. First steps.mp4 | 3.0 MB |
| 002. Chapter 1. Discovering graph neural networks.mp4 | 30.8 MB |
| 003. Chapter 1. Graph-based learning.mp4 | 57.8 MB |
| 004. Chapter 1. GNN applications Case studies.mp4 | 21.4 MB |
| 005. Chapter 1. When to use a GNN.mp4 | 25.9 MB |
| 006. Chapter 1. Understanding how GNNs operate.mp4 | 23.7 MB |
| 007. Chapter 1. Summary.mp4 | 6.6 MB |
| 008. Chapter 2. Graph embeddings.mp4 | 72.2 MB |
| 009. Chapter 2. Creating embeddings with a GNN.mp4 | 34.0 MB |
| 010. Chapter 2. Using node embeddings.mp4 | 50.3 MB |
| 011. Chapter 2. Under the Hood.mp4 | 62.4 MB |
| 012. Chapter 2. Summary.mp4 | 6.4 MB |
| 013. Part 2. Graph neural networks.mp4 | 3.0 MB |
| 014. Chapter 3. Graph convolutional networks and GraphSAGE.mp4 | 84.0 MB |
| 015. Chapter 3. Aggregation methods.mp4 | 51.3 MB |
| 016. Chapter 3. Further optimizations and refinements.mp4 | 39.9 MB |
| 017. Chapter 3. Under the hood.mp4 | 64.8 MB |
| 018. Chapter 3. Amazon Products dataset.mp4 | 17.1 MB |
| 019. Chapter 3. Summary.mp4 | 7.9 MB |
| 020. Chapter 4. Graph attention networks.mp4 | 14.7 MB |
| 021. Chapter 4. Exploring the review spam dataset.mp4 | 48.4 MB |
| 022. Chapter 4. Training baseline models.mp4 | 25.2 MB |
| 023. Chapter 4. Training GAT models.mp4 | 37.7 MB |
| 024. Chapter 4. Under the hood.mp4 | 32.0 MB |
| 025. Chapter 4. Summary.mp4 | 5.9 MB |
| 026. Chapter 5. Graph autoencoders.mp4 | 32.5 MB |
| 027. Chapter 5. Graph autoencoders for link prediction.mp4 | 39.2 MB |
| 028. Chapter 5. Variational graph autoencoders.mp4 | 34.3 MB |
| 029. Chapter 5. Generating graphs using GNNs.mp4 | 48.8 MB |
| 030. Chapter 5. Under the hood.mp4 | 32.3 MB |
| 031. Chapter 5. Summary.mp4 | 6.3 MB |
| 032. Part 3. Advanced topics.mp4 | 4.4 MB |
| 033. Chapter 6. Dynamic graphs Spatiotemporal GNNs.mp4 | 26.1 MB |
| 034. Chapter 6. Problem definition Pose estimation.mp4 | 38.6 MB |
| 035. Chapter 6. Dynamic graph neural networks.mp4 | 28.6 MB |
| 036. Chapter 6. Neural relational inference.mp4 | 82.7 MB |
| 037. Chapter 6. Under the hood.mp4 | 32.6 MB |
| 038. Chapter 6. Summary.mp4 | 4.7 MB |
| 039. Chapter 7. Learning and inference at scale.mp4 | 25.2 MB |
| 040. Chapter 7. Framing problems of scale.mp4 | 41.9 MB |
| 041. Chapter 7. Techniques for tackling problems of scale.mp4 | 16.6 MB |
| 042. Chapter 7. Choice of hardware configuration.mp4 | 31.0 MB |
| 043. Chapter 7. Choice of data representation.mp4 | 17.1 MB |
| 044. Chapter 7. Choice of GNN algorithm.mp4 | 24.3 MB |
| 045. Chapter 7. Batching using a sampling method.mp4 | 26.2 MB |
| 046. Chapter 7. Parallel and distributed processing.mp4 | 28.7 MB |
| 047. Chapter 7. Training with remote storage.mp4 | 25.7 MB |
| 048. Chapter 7. Graph coarsening.mp4 | 26.9 MB |
| 049. Chapter 7. Summary.mp4 | 5.6 MB |
| 050. Chapter 8. Considerations for GNN projects.mp4 | 23.8 MB |
| 051. Chapter 8. Designing graph models.mp4 | 57.1 MB |
| 052. Chapter 8. Data pipeline example.mp4 | 76.4 MB |
| 053. Chapter 8. Where to find graph data.mp4 | 12.9 MB |
| 054. Chapter 8. Summary.mp4 | 12.3 MB |
| 055. appendix A. Discovering graphs.mp4 | 53.3 MB |
| 056. appendix A. Graph representations.mp4 | 68.5 MB |
| 057. appendix A. Graph systems.mp4 | 14.6 MB |
| 058. appendix A. Graph algorithms.mp4 | 11.7 MB |
| 059. appendix A. How to read GNN literature.mp4 | 9.7 MB |
| Bonus Resources.txt | 70 bytes |
Name
DL
Uploader
Size
S/L
Added
-
15.0 MB
[0
/
1]
2023-07-01
| Uploaded by FreeCourseWeb | Size 15.0 MB | Health [ 0 /1 ] | Added 2023-07-01 |
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14.5 MB
[11
/
1]
2025-01-11
| Uploaded by indexFroggy | Size 14.5 MB | Health [ 11 /1 ] | Added 2025-01-11 |
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49.7 MB
[14
/
3]
2025-02-24
| Uploaded by indexFroggy | Size 49.7 MB | Health [ 14 /3 ] | Added 2025-02-24 |
NOTE
SOURCE: Graph Neural Networks in Action Video Edition
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