Browse Lessons

Stanford CS25: V3 I Generalist Agents in Open-Ended Worlds

Stanford CS25: V3 I Low-level Embodied Intelligence w/ Foundation Models

Stanford CS224W: Machine Learning w/ Graphs I 2023 I Trustworthy Graph AI, Rex Ying

Stanford CS224W: Machine Learning w/ Graphs I 2023 I Geometric Graph Learning, Minkai Xu

Stanford CS224W: Machine Learning w/ Graphs I 2023 I Advanced Topics in GNNs

Stanford CS224W: Machine Learning w/ Graphs I 2023 I GNNs for Recommender Systems

Stanford CS224W: Machine Learning w/ Graphs I 2023 I Knowledge Graph Embeddings

Stanford CS224W: Machine Learning w/ Graphs I 2023 I Machine Learning with Heterogeneous Graphs

Stanford CS224W: Machine Learning w/ Graphs I 2023 I Label Propagation on Graphs

Stanford CS224W: Machine Learning w/ Graphs I 2023 I Graph Neural Networks

Course Overview: Human-Centered Design for Digital Transformation - with Julie Stanford

Stanford Seminar - How to change environments to regulate problematic behaviors

Ask About AI: Professor Chris Manning on Explainability in AI Models

Statistical Learning: 10.Py Document Classification and Recurrent Neural Networks I 2023

Statistical Learning: 13.Py False Discovery Rate I 2023

Statistical Learning: 13.Py Multiple Testing I 2023

Statistical Learning: 12.Py Application: NCI60 Data I 2023

Statistical Learning: 12.Py Clustering I 2023

Statistical Learning: 12.Py Principal Components I 2023

Statistical Learning: 13.Py Multiple Testing and Resampling I 2023

Statistical Learning: 10.Py Multilayer Model: MNIST Digit Data I 2023

Statistical Learning: 9.Py Support Vector Machines I 2023

Statistical Learning: 11.Py Cox Model: Brain Cancer Data I 2023

Statistical Learning: 10.Py Convolutional Neural Network: CIFAR Image Data I 2023