Published inData Science CollectiveGraph Neural Networks Part 3. How GraphSAGE Handles Changing Graph StructureAnd how you can use it for large graphsJun 5Jun 5
Published inData Science CollectiveGraph Neural Networks Part 4: Teaching Models to Connect the DotsHeuristic and GNN-based approaches to Link PredictionJun 5Jun 5
Published inTDS ArchiveYou Think 80% Means 80%? Why Prediction Probabilities Need a Second LookUnderstand the gap between predicted probabilities and real-world outcomesJan 14A response icon2Jan 14A response icon2
Published inTDS ArchiveGraph Neural Networks Part 2. Graph Attention Networks vs. GCNsA model that pays attention to your graphOct 8, 2024Oct 8, 2024
Published inTDS ArchiveGraph Neural Networks Part 1. Graph Convolutional Networks ExplainedNode classification with Graph Convolutional NetworksOct 1, 2024A response icon2Oct 1, 2024A response icon2
Published inbigdatarepublicExploring the Uncharted Territories of Math in Data ScienceBeyond the usual topics like statistics, calculus, and linear algebraMay 27, 2024May 27, 2024
Published inTDS ArchiveCombining Storytelling and Design for Unforgettable PresentationsHow to craft slide decks that stand outApr 18, 2024A response icon3Apr 18, 2024A response icon3
Published inTDS ArchiveMonte Carlo Methods DecodedSolving complex problems with simulationsFeb 16, 2024A response icon3Feb 16, 2024A response icon3
Published inTDS ArchiveFinding Optimal Solutions with Branch and BoundA powerful algorithm for solving discrete optimization problemsDec 5, 2023A response icon2Dec 5, 2023A response icon2
Published inTDS ArchiveIs This the Solution to P-Hacking?E-values, a better alternative for p-valuesNov 16, 2023A response icon4Nov 16, 2023A response icon4