**This page will be updated in September 2024. Enjoy your summer break until then 😎.**

- If you are
**Japanese student,**please also register at the NU-EMI project for this course. - We will use a
**Discord server**for communication and for sharing materials & code. - We will use TACT for homework submission.

****This course is targeted at any student of Nagoya University who is interested in some of the mathematics used in machine learning. As a background I expect that the students have some background in Linear Algebra and Calculus (e.g. Linear Algebra I & Calculus I from the G30 Program). I do not expect that the students can already program, but if you do not have any Python experience you might need to do a basic course by yourself at the beginning (or in the summer break). If you took the Data Science Exercise B then this course is perfect for you. If you have any questions or suggestions on the course please feel free to contact me.

**Materials**

- Coming soon

**Content (tentative)**

Machine learning became a popular and really broad field in recent years. Machine learning algorithms are used in a wide variety of applications, such as email filtering, computer vision, medicine, language translation, computer games, economic, etc.. The goal of this course is to give a brief introduction into machine learning with a focus on the mathematical tools used.

We will probably cover at least the following topics:

- Introduction to machine learning and programming in Python
- Supervised learning: Linear & Logistic regression, Neural networks
- Unsupervised learning: PCA, Autoencoder
- Reinforcement Learning: Q-Learning

**Grading**

The grade will we based on homework submissions and one final project.

The credits follow the

**new rule for SML classes**. (SML=Special mathematics lecture)

Please contact me via email if you have any questions.

**Course schedule**

**(tentative)**

**Lecture**:

- Time: Monday 6th period (18:15-19:45). First lecture: October 7th.
- Room: A250 (Computer room) in Science Building A (D3 (2) on the Nagoya University Campus map)

**Tutorial:**

- Time: TBA
- Room: A250 (Same as the lecture)

Last update: 18th August 2024.