Lecture schedule
Lecture schedule is
- Tuesday, Jan 20: Introduction
- Thursday, Jan 22: Neural networks / Deep learning (part 1a)
- Homework 1 assigned (Due Thursday, Jan 22) (instructions for accessing)
- Tuesday, Jan 27: Neural networks / Deep learning (part 1b)
- Thursday, Jan 29: Neural networks / Deep learning (part 2a)
- Tuesday, Feb 3: Neural networks / Deep learning (part 2b)
- Thursday, Feb 5: Reinforcement learning (part 1a)
- Tuesday, Feb 10: Reinforcement learning (part 1b)
- Thursday, Feb 12: Reinforcement learning (part 2a)
- Homework 2 assigned (Due Tuesday, Feb 10) (instructions for accessing)
- Tuesday, Feb 17: Reinforcement learning (part 2b)
- Thursday, Feb 19: Reinforcement learning (part 3a)
- Tuesday, Feb 24: Reinforcement learning (part 3b)
- Thursday, Feb 26: Bayesian modeling (part 1a)
- Homework 3 assigned (Due Tuesday, Feb 17) (instructions for accessing)
- Tuesday, Mar 3: Bayesian modeling (part 1b)
- Thursday, Mar 5: Bayesian modeling (part 2a)
- Project proposal is due
- Tuesday, Mar 10: Bayesian modeling (part 2b)
- Thursday, Mar 12: Model comparison and fitting (part a)
- Tuesday, Mar 17: Model comparison and fitting (part b)
- Thursday, Mar 19: Categorization (part a)
- Homework 4 assigned (Due Thursday, Feb 26) (instructions for accessing)
- Tuesday, Mar 24: Categorization (part b)
- Thursday, Mar 26: Probabilistic Graphical models (part a)
- Tuesday, Mar 31: Probabilistic Graphical models (part b)
- Thursday, Apr 2: Casual interventions and active learning (part a)
- Tuesday, Apr 7: Casual interventions and active learning (part b)
- Thursday, Apr 9: No Class, Thanksgiving Break
- Tuesday, Apr 14: Program induction and language of thought models (part a)
- Thursday, Apr 16: Program induction and language of thought models (part b)
- Tuesday, Apr 21: TBD
- Thursday, Apr 23: TBD
- Tuesday, Apr 28: TBD
- Thursday, Apr 30: TBD
- Tuesday, May 5: TBD
- Final project due (Due Tuesday, May 5)