# machine_learning_2026_spring

**Repository Path**: lundechen/machine_learning_2026_spring

## Basic Information

- **Project Name**: machine_learning_2026_spring
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 4
- **Forks**: 2
- **Created**: 2026-04-24
- **Last Updated**: 2026-07-08

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# ML01 Machine Learning, UTSEUS, Shanghai University

## QR Code

![](/img/qr.jpg)

## Language

English. For everything.

### Laptop

For each session, **please bring your own Laptop!**. Please bring your headphone as well, because you will watch videos.


## Sessions (Main)

For the main sessions, each session will be:
- 1h of lecture
- 1h of code
- 1h of practice

We have 6 hours for each week, 
hence two main session each week.

### Session 1
- Linear Regression

### Session 2
- Logistic Regression (for classification)

### Session 3, 4, 5
- Neural networks

### Session 6, 7
- Model selection

## Sessions (Extra)

### Session 8 and after

- Transformer/Attention is all you need

- CNN, ResNet

- GAN, adversarial attack

- AutoEncoder




## Score

Denoting your Final Exam score as `T`, your project score as `P`, your final score will be 

```python
0.7 * T + 0.3 * P
```

For final exams `T`:
- around 70% will be on session 1 to session 7 (main sessions, from linear regression, logistic regression, neural networks up to model selections; questions will be more in depth; lecture and code; a little bit of practice will be in the final exam as well). Some of the questions will come from BagOfQuestions folder.
- around 30% will be easy questions for extra sessions. 
- no materials will be allowed (no books, no sheets, no dictionaries, no anything) during the final exam.

Final exam will take place on one of the days of the two weeks of exam weeks.

Duration: 2 hours.

![](./img/exam.jpg)


大家注意，考试时，请在试卷第一页左上角写上自己的座位号。座位号在座位表里，用小括号括着，比如（1）（2）（3）这样，依次类推。

Everyone, please note that during the exam, write your seat number in the upper left corner of the first page of the test paper. The seat numbers are shown in parentheses on the seating chart, e.g., (1), (2), (3), and so on.

![](./img/seatnumber.jpg)


### Distribution of notes
The distribution of notes is as follows:
- 10% A (90-100)
- 20% A- (85-89)
- 30% B (80-84)
- 20% C (75-79)
- 20% D/E/F

Historical failure rates:
- 2021: 10%
- 2023: 10%
- 2025: 15%
- 2026: 20.8%



#### Zen of Python

https://peps.python.org/pep-0020/

```text
Beautiful is better than ugly.

Explicit is better than implicit.

Simple is better than complex.

Complex is better than complicated.

Flat is better than nested.

Sparse is better than dense.

Readability counts.

Special cases aren't special enough to break the rules.

Although practicality beats purity.

Errors should never pass silently.

Unless explicitly silenced.

In the face of ambiguity, refuse the temptation to guess.

There should be one-- and preferably only one --obvious way to do it.

Although that way may not be obvious at first unless you're Dutch.

Now is better than never.

Although never is often better than *right* now.

If the implementation is hard to explain, it's a bad idea.

If the implementation is easy to explain, it may be a good idea.

Namespaces are one honking great idea -- let's do more of those!
```

## Asking questions :question:

### Leveraging **[Gitee Issue](https://gitee.com/lundechen/cpp/issues)** for asking questions
By default, you should ask questions via **[Gitee Issue](https://gitee.com/lundechen/cpp/issues)**. Here is how:
- https://www.bilibili.com/video/BV1364y1h7sb/

### Principe
Here is the principle for asking questions:

>  **Google/ChatGPT First, Peers Second, Profs Last.**

You are expected to ask questions via **[Gitee Issue](https://gitee.com/lundechen/cpp/issues)**. However, as a **secondary**  (and hence, less desirable, less encouraged) choice, you could also ask questions in the WeChat group.

> Why Gitee Issue? Because it's simply more **professional**, and better in every sense.

In Gitee Issue and the WeChat group, questions will be answered selectively. 

Questions won't be answered if:
- they could be solved on a simple Google search
- they are out of the scope of the course
- they are well in advance of the progress of the course
- professors think that it's not interesting for discussion

### Regarding personal WeChat chats:
- **Questions asked in personal WeChat chats will NOT be answered.**

Learning how to use Google & Baidu & Bing & ChatGTP to solve computer science problems is an important skill you should develop during this course.

For private questions, please send your questions by email to:
- lundechen@shu.edu.cn (Lunde Chen)

### Office visit

Office visit is NOT welcome unless you make an appointment at least one day in advance.

## Online resources

1. 吴恩达机器学习系列：
    - https://www.bilibili.com/video/BV164411b7dx
1. 吴恩达深度学习系列：
    - https://www.bilibili.com/video/BV164411m79z