|
Stanford CS329A Self-Improving AI Agents | Part 4 | Learning from Feedback with Tools/Code
|
|
1
|
3
|
3 August 2026
|
|
Stanford CS329A Self-Improving AI Agents | Part 1 | Course Overview
|
|
1
|
0
|
3 August 2026
|
|
Stanford CS329A Self-Improving AI Agents | Part 7 | Self-Improvement and Deep Research Agents
|
|
1
|
1
|
3 August 2026
|
|
Stanford CS329A Self-Improving AI Agents | Part 5 | Planning and Multi-Step Reasoning
|
|
1
|
0
|
3 August 2026
|
|
Stanford CS329A Self-Improving AI Agents | Part 6 | Train Time Scaling/Scaling RL
|
|
1
|
2
|
3 August 2026
|
|
Stanford CS329A Self-Improving AI Agents | Part 3 | Robust Verification
|
|
1
|
1
|
3 August 2026
|
|
Stanford CS329A Self-Improving AI Agents | Part 2 | Test-Time Compute Scaling
|
|
1
|
4
|
3 August 2026
|
|
Stanford CS329A Self-Improving AI Agents | Part 9 | Future Research Areas
|
|
1
|
0
|
3 August 2026
|
|
Stanford CS329A Self-Improving AI Agents | Part 8 | Agentic Evaluations and Long Horizon Tasks
|
|
1
|
1
|
3 August 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 20: GMM (EM), PCA
|
|
1
|
6
|
31 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 18: GMM (EM), PCA
|
|
1
|
0
|
31 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 16: Basic Concept in RL, Policy Gradient
|
|
1
|
1
|
31 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 14: Transformers, In-Context Learning
|
|
1
|
1
|
31 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 13: LLMs, Next-Word Prediction Loss
|
|
1
|
0
|
31 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 12: Representation Learning
|
|
1
|
0
|
31 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 11: Diffusion Models
|
|
1
|
0
|
31 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 10: GMM (EM), PCA
|
|
1
|
1
|
31 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 9: K-Means and GMM (non-EM)
|
|
1
|
1
|
31 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 8: Neural Networks 2 (Backprop)
|
|
1
|
4
|
31 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 7: Neural Networks 1 (Architecture)
|
|
1
|
4
|
31 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 6: Dataset Split, ML Advice
|
|
1
|
1
|
30 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 5: Gaussian Discriminant Analysis
|
|
1
|
3
|
30 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 4: Exponential Family, GLMs classification
|
|
1
|
2
|
30 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 3: Weighted Least Squares
|
|
1
|
2
|
30 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 2: Supervised Learning Setup
|
|
1
|
6
|
30 July 2026
|
|
Stanford CS229 Machine Learning | Spring 2026 | Lecture 1: Introduction
|
|
1
|
1
|
29 July 2026
|
|
Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | The GPU Economy
|
|
1
|
1
|
23 July 2026
|
|
Stanford CS547 HCI Seminar | Spring 2026 | Promoting Agency in Human-AI Interaction
|
|
1
|
1
|
23 July 2026
|
|
Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Economics of Generative AI
|
|
1
|
3
|
17 July 2026
|
|
Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Applications, AI in Life Sciences
|
|
1
|
0
|
17 July 2026
|