Stanford CS224W: Machine Learning with Graphs
4.0
(2)
29 learners
What you'll learn
This course includes
- 22.3 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 60 lessons • 22.3 hours of video
Stanford CS224W: Machine Learning with Graphs
60 lessons
• 22.3 hours
Stanford CS224W: Machine Learning with Graphs
60 lessons
• 22.3 hours
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.1 - Why Graphs 11:55
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.2 - Applications of Graph ML 20:27
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.3 - Choice of Graph Representation 20:27
- Stanford CS224W: ML with Graphs | 2021 | Lecture 2.1 - Traditional Feature-based Methods: Node 27:30
- Stanford CS224W: ML with Graphs | 2021 | Lecture 2.2 - Traditional Feature-based Methods: Link 16:47
- Stanford CS224W: ML with Graphs | 2021 | Lecture 2.3 - Traditional Feature-based Methods: Graph 20:10
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 3.1 - Node Embeddings 14:44
- Stanford CS224W: ML with Graphs | 2021 | Lecture 3.2-Random Walk Approaches for Node Embeddings 27:07
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 3.3 - Embedding Entire Graphs 18:04
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 4.1 - PageRank 27:10
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 4.2 - PageRank: How to Solve? 20:41
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 4.3 - Random Walk with Restarts 13:31
- Stanford CS224W: ML with Graphs | 2021 | Lecture 4.4 - Matrix Factorization and Node Embeddings 12:48
- Stanford CS224W: ML with Graphs | 2021 | Lecture 5.1 - Message passing and Node Classification 18:34
- Stanford CS224W: ML with Graphs | 2021 | Lecture 5.2 - Relational and Iterative Classification 29:20
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 5.3 - Collective Classification 24:26
- Stanford CS224W: ML with Graphs | 2021 | Lecture 6.1 - Introduction to Graph Neural Networks 10:31
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 6.2 - Basics of Deep Learning 29:31
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 6.3 - Deep Learning for Graphs 35:41
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 7.1 - A general Perspective on GNNs 05:51
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 7.2 - A Single Layer of a GNN 40:09
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 7.3 - Stacking layers of a GNN 18:11
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 8.1 - Graph Augmentation for GNNs 27:50
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 8.2 - Training Graph Neural Networks 40:19
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 8.3 - Setting up GNN Prediction Tasks 17:49
- Stanford CS224W: ML with Graphs | 2021 | Lecture 9.1 - How Expressive are Graph Neural Networks 25:21
- Stanford CS224W: ML with Graphs | 2021 | Lecture 9.2 - Designing the Most Powerful GNNs 31:52
- Stanford CS224W: ML with Graphs | 2021 | Lecture 10.1-Heterogeneous & Knowledge Graph Embedding 34:57
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 10.2 - Knowledge Graph Completion 07:16
- Stanford CS224W: ML with Graphs | 2021 | Lecture 10.3 - Knowledge Graph Completion Algorithms 34:31
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 11.1 - Reasoning in Knowledge Graphs 16:53
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 11.2 - Answering Predictive Queries 12:39
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 11.3 - Query2box: Reasoning over KGs 38:20
- Stanford CS224W: ML with Graphs | 2021 | Lecture 12.1-Fast Neural Subgraph Matching & Counting 35:40
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 12.2 - Neural Subgraph Matching 24:54
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 12.3 - Finding Frequent Subgraphs 25:54
- Stanford CS224W: ML with Graphs | 2021 | Lecture 13.1 - Community Detection in Networks 22:14
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 13.2 - Network Communities 17:41
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 13.3 - Louvain Algorithm 15:20
- Stanford CS224W: ML with Graphs | 2021 | Lecture 13.4 - Detecting Overlapping Communities 23:57
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 14.1 - Generative Models for Graphs 20:28
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 14.2 - Erdos Renyi Random Graphs 20:00
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 14.3 - The Small World Model 10:29
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 14.4 - Kronecker Graph Model 18:03
- Stanford CS224W: ML with Graphs | 2021 | Lecture 15.1 - Deep Generative Models for Graphs 15:44
- Stanford CS224W: ML with Graphs | 2021 | Lecture 15.2 - Graph RNN: Generating Realistic Graphs 24:52
- Stanford CS224W: ML with Graphs | 2021 | Lecture 15.3 - Scaling Up & Evaluating Graph Gen 15:29
- Stanford CS224W: ML with Graphs | 2021 | Lecture 15.4 - Applications of Deep Graph Generation 13:35
- Stanford CS224W: ML with Graphs | 2021 | Lecture 16.1 - Limitations of Graph Neural Networks 11:10
- Stanford CS224W: ML with Graphs | 2021 | Lecture 16.2 - Position-Aware Graph Neural Networks 12:41
- Stanford CS224W: ML with Graphs | 2021 | Lecture 16.3 - Identity-Aware Graph Neural Networks 20:01
- Stanford CS224W: ML with Graphs | 2021 | Lecture 16.4 - Robustness of Graph Neural Networks 22:39
- Stanford CS224W: ML with Graphs | 2021 | Lecture 17.1 - Scaling up Graph Neural Networks 14:51
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 17.2 - GraphSAGE Neighbor Sampling 16:50
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 17.3 - Cluster GCN: Scaling up GNNs 19:18
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 17.4 - Scaling up by Simplifying GNNs 18:40
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 18 - GNNs in Computational Biology 01:21:19
- Stanford CS224W: ML with Graphs | 2021 | Lecture 19.1 - Pre-Training Graph Neural Networks 20:07
- Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 19.2 - Hyperbolic Graph Embeddings 31:47
- Stanford CS224W: ML with Graphs | 2021 | Lecture 19.3 - Design Space of Graph Neural Networks 18:10
