2023-Syllabus (public).xlsx

	A	B	C
1	Date	Tue	Thur
2	9/12	Lecture: Intro & Linear Algebra	Lecture: Probability & Info Theory
3	9/19	Lecture: Numerical Optimization	Quiz (From Linear Algebra to Numerical Optimization)
4	9/26	Lecture: Learning Theory and Regularization	No Lecture (Teachers' day)
5	9/26	Lecture: Learning Theory and Regularization	Data Exploration & PCA (Bonus Lab)、Decision Trees & Random Forest (Bonus Lab) Perceptron & Adaline (Bonus Lab)、Regression (Bonus Lab)
6	10/3	Lecture: Probabilistic Models	No Lecture (Class Cancelled)
7	10/10	No Lecture (National Day)	Lab: Regularization (Ridge, LASSO, RANSAC)
8	10/10	No Lecture (National Day)	Competition 1: Text Feature Engineering
9	10/17	Lecture: Neural Networks: Design	Lab: Tensorflow 101 (Tutorial, No assignment)
10			Lab: Logistic Regression, Metrics
11			Suggested Reading: Lecture 7 & 8 SVMs & Scikit-Learn Pipelines (Bonus Lab)、CV & Ensembling (Bonus Lab)
12	10/24	Lecture: Neural Networks: Optimization & Regularization	Lab: Word2Vec
13	10/31	Lecture: Convolutional Neural Networks	Competition 1: Show Off
14	10/31	Lecture: Convolutional Neural Networks	Lab: Convolutional Neural Networks & Data Pipelines
15	11/7	Lecture: Convolutional Neural Networks	Lab: Visualization, Style Transfer & Save and Load Models
16	11/7	Lecture: Convolutional Neural Networks	Competition 2: Object Detection
17	11/14	Lecture: Recurrent Neural Networks & Transformers	Lab: Seq2Seq & Attention & Machine Translation
18	11/21	Lecture: Recurrent Neural Networks & Transformers	Lab: Image captioning
19	11/28	Lecture: Unsupervised Learning & Generative AI	Lab: Autoencoders & GANs
20	11/28	Lecture: Unsupervised Learning & Generative AI	Competition 3: Reverse Image Captioning
21	12/5	Lecture: Unsupervised Learning & Generative AI	Competition 2: Show Off
22	12/12	Lecture: Reinforcement Learning	Lab: Diffusion Models (Bonus Lab)
23	12/19	Lecture: Deep Reinforcement Learning	Lab: Q-learning
24	12/26	Application: Neural Search and Recommender Systems	Lab: DQN & Policy Gradient
25	1/2	Final (From Learning Theory to Deep RL)	Competition 3: Show Off
26	1/2	Final (From Learning Theory to Deep RL)	Competition 4: Recommender Systems
27	1/9	No Lecture	No Lecture
28	1/9	No Lecture	No Lecture
29		Competition 4: Show Off
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100