Instructors: Brenden Lake and Todd Gureckis
Please note that these videos are a good but imperfect substitute for attending live lectures. We change the slides from year to year.
- Introduction (video)
- Neural networks / Deep learning (part 1)(video)
- Neural networks / Deep learning (part 2)(video)
- Reinforcement learning (part 1)(video)
- Reinforcement learning (part 2)(video)
- Reinforcement learning (part 3)(video)
- Bayesian modeling (part 1)(video)
- Bayesian modeling (part 2)(video
- Model comparison and fitting, tricks of the trade(video)
- Categorization (video)
- Probabilistic Graphical models (video)
- Information sampling and active learning (video)
- Program induction and language of thought models (video)
- Computational Cognitive Neuroscience (video)
- Final summary (video)