高级机器学习（Advanced Machine Learning）
- 教师: 郭兰哲（guolz@nju.edu.cn）
- 授课对象: 智能科学与技术学院 研究生
- 地点: 周三5-6节，南雍楼-东122
- 教材: 周志华，机器学习，清华大学出版社
考核方式
- 课堂汇报：选择一个机器学习研究方向制作PPT在课堂上进行口头报告(10-15mins)
- 论文综述：选择一个机器学习研究方向进行综述介绍，论文模版可参考《计算机学报》 以上两部分各占50%。
课程材料
#Week |
Slides |
Week 4 |
General Introduction |
Week 5 |
Model Evaluation and SelectionLinear Model |
Week 6 |
SVM, Decision Tree, Bayes Classifier, Clustering, Dimensional Reduction |
Week 7 |
Neural Networks and Deep Learning |
Week 8 |
Ensemble LearningFeature Selection |
Week 9 |
Semi-Supervised Learning |
Week 10 |
Safe Semi-Supervised Learning |
Week 11 |
Transfer Learning |
Week 12 |
Probabilistic Graphical Model |
Week 13 |
Reinforcement Learning |
Week 14 |
Reinforcement Learning |