====== ML Draft ======


===== 教学计划 =====






| 序号 | 主题 | 时间 | Slides |
| 1 | Introduction | wk1 |  |
| 2 | Shallow Learning | wk2 |  |
| 3 | Deep Learning | wk3 |  |
| 4 | Reinforcement Learning | wk4 |  |
| 5 | Big Data & ML | wk5 |  |
| 6 | Empirical Asset Pricing & ML | wk6 |  |
| 7 | Causal Inference & ML | wk7 |  |
| 8 | LLMs & Agents | wk8 |  |

| 序号 | 主题 | 时间 | Slides |
| 1 | A Brief Introduction to ML | wk1 | [[http://kktim.cn/teaching/mlinfin/MLinFin-L01-Introduction-slides.html|L01-introduction-slides]] |
| 2 | Shallow Learning Algorithms | wk2-wk3 | [[http://kktim.cn/teaching/mlinfin/MLinFin-L02-Regression-slides.html|L02-regression-slides]]\\ [[http://kktim.cn/teaching/mlinfin/MLinFin-L03-Classification-slides.html|L03-classification-slides]]\\ [[http://kktim.cn/teaching/mlinfin/MLinFin-L04-Trees-slides.html|L04-trees-and-ensemble-learning-slides]]\\ [[http://kktim.cn/teaching/mlinfin/MLinFin-L05-Unsupervised-Learning-slides.html|L05-unsupervised-learning-slides]] |
| 3 | Deep Neural Networks | wk4 | [[http://kktim.cn/teaching/mlinfin/MLinFin-L06-Deep-Learning-slides.html|L06-deep-learning-I-slides]], [[http://kktim.cn/teaching/mlinfin/MLinFin-L06-Deep-Learning-II-slides.html|L06-Deep-Learning-II-slides]] |
| 4 | Literature Studies | wk5-wk8 | [[http://kktim.cn/teaching/mlinfin/MLinFin-LXX-Presentation-schedule-slides.html|Presentation Schedule]] |
| 5 | MDP & Reinforcement Learning | by yourself | [[http://kktim.cn/teaching/mlinfin/MLinFin-L06-MDP-in-Finance-slides.html|L07a-MDP-slides]]\\  [[http://kktim.cn/teaching/mlinfin/MLinFin-L07-Advances-of-RL-in-Finance-slides.html|L07b-RL-slides]] |
| 6 | SP1: Machine Learning & Asset Pricing & Financial Bigdata | by yourself | [[https://www.nber.org/papers/w31502|NBER Working Paper: Financial Machine Learning]] |
| 7 | ST2: Machine Learning and Causal Inference | by yourself | [[https://www.bilibili.com/video/BV19Y4y117st/?vd_source=0a4eefc320d2637b710b584ebc1ce471|NBER SI 2015 Methods Lectures - Machine Learning for Economists]]\\ [[https://www.bilibili.com/video/BV1KY4y127Qs/?vd_source=0a4eefc320d2637b710b584ebc1ce471|2018 AEA Continuing Education Webcasts: Machine Learning and Econometrics (Susan Athey, Guido Imbens)]]\\ [[https://www.gsb.stanford.edu/faculty-research/centers-initiatives/sil/research/methods/ai-machine-learning/short-course|Machine Learning & Causal Inference: A Short Course]] |