Repository to accompany the substack Data For Science
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25. Graph Neural Networks 101: Predicting Molecular Properties from Scratch - Graph Neural Networks 101.ipynb
24. k-core Decomposition - k-core.ipynb
23. Network Attacks - Network Attacks.ipynb
22. Kahn's Algorithm for Topological Sorting - Topological Sorting.ipynb
21. Prim's Minimum Spanning Tree Algorithm - Prim's MST Algorithm.ipynb
20. Neighborhood Overlap and Edge Weights - Edge Weight and Network structure.ipynb
19. Bipartite Graphs 101 - Bipartite 101.ipynb
18. Epidemic Models
17. Community Structure and Network Modularity - Community Detection.ipynb
16. Markov Chains and PageRank - PageRank.ipynb
15. Network Assortativity and the Configurational Model - Degree Correlations and the Configurational Model.ipynb
14. Barabasi-Albert Model and Preferential Attachment - BA Model and Preferential Attachment.ipynb
13. The Watts-Strogatz Model and the Small World Effect - WS and the Small World Effect.ipynb
12. Erdős-Rényi Model and Clustering Coefficient - ER and Clustering Coefficient.ipynb
11. Network Motifs: Frequent patterns in Graphs - motifs.ipynb
10. Bitcoin Transaction Network: Networks on the blockchain - Blockchain.ipynb
9. Graph Components: Strongly and Weakly Connected Components - Components.ipynb
8. Node Centrality: Degree, Closeness, and Betweenness Centrality - Node Centrality.ipynb
7. Graph Embeddings 101: From word2vec to node2vec, and beyond - node2vec.ipynb
6. Structural Causal Models: Reasoning with DAGs
5. Searching Graphs: Or how to get turn by turn directions from Open Street Map - Search.ipynb
4. Word Networks for Language Generation - n-grams.ipynb
3. Understanding DBSCAN and K-NN with Random Geometric Graphs - Random Networks.ipynb
2. Graphs 101 - A deep look at the airline transportation network - Graphs 101 - Airline Network.ipynb
1. Graph Algorithms for Data Science
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