MLAPP Reading Group of 2025 Spring 2025年春季第三届“斛兵”机器学习读书会

Introduction 介绍

MLAPP reading group is for HFUT junior students to spend a semester to read the MLAPP book. We believe it is imperative to get a general and deep understanding of machine learning. We will embrace a student-led reporting approach with tutor guidance and review, enabling us to grasp cutting-edge knowledge in machine learning and related fields at an accelerated pace, surpassing the foundational content of an undergraduate machine learning course.

“斛兵”机器学习读书会是供合肥工业大学的机器学习领域的入门学生系统的一个学期内学习完毕《概率机器学习》这本书，这对于更好更广泛的理解机器学习至关重要。我们将采用学生主导并汇报、导师指导点评的方式，并以远快于本科机器学习基础课程的速度学习机器学习及相关领域的前沿知识。

After completing the reading group, you will basically have the foundation to engage in artificial intelligence-related scientific research.

学成之后将基本具备从事人工智能相关科研的基础。

Stay tuned for MLAPP Reading Group of 2025 Spring! 敬请期待2025年春季第三届“斛兵”机器学习读书会！

The best presenters will receive awards and small gifts from Dean Richang Hong! Stay tuned! 最佳报告人将会获得洪院长颁发的奖品，敬请期待！

We have finished the reading group meeting of 2023! 第二届2024年春季学习读书会圆满完成！

We have finished the reading group meeting of 2023! See this news in Chinese.

第一届2023年春季学习读书会圆满完成并为最佳报告人颁奖！请查看新闻稿。

Resources

MLAPP: https://probml.github.io/pml-book/
PRML: https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf
概率机器学习 by 朱军: https://newbooks.lib.pku.edu.cn/bookdetail.jsp?bookid=546619
Deep Learning: https://www.deeplearningbook.org/
统计学习方法 by 李航: https://book.douban.com/subject/33437381/
动手学深度学习: https://zh.d2l.ai/

Shedule （TBD）

Number	Content	Materials	Presenter	Date
1	Book1- Introduction & Foundation	mlapp-1,2. prml-1,2	Wenbo Hu
2	Book1 - Linear Models	mlapp-7,8. prml-chap3,4.
3	Book1 - Deep Neural Networks	mlapp-16. prml-5,28.
4	Book1 - Nonparametric Methods	mlapp-14,16. prml-6,7
5	Book1 - Beyond Supervised Learning	mlapp-25
6	Book2 - Fundamentals (Probability, Bayesian Statistics, Information Theory)
7	Book2 - Fundamentals (Probablistic Graphical Models)	mlapp-19, prml-8
8	Book2 - Fundamentals (Optimization)
9	Book2 - Inference (Overview, SSM, Exact Inference)	mlapp-18,19
10	Book2 - Inference (Variational Inference)
11	Book2 - Inference (Monte Carlo)	mlapp-10, 12
12	Book2 - Prediction	mlapp-15
13	Book2 - Generation
14	Book2 - Discovery
15	Book2 - Action

2. 线性模型与朴素贝叶斯方法 3. 广义线性模型与对数几率回归 4. 深度神经网络 5. 支持向量机与核方法 6. 聚类与降维 7. 集成学习 8. 学习理论 9. 概率图模型 10. 变分推断 11. 蒙特卡洛方法 12. 高斯过程 13. 深度生成模型 14. 强化学习

Prerequisite 要求

Have taken calculus, linear algebra, probability and statistics, and any programming language. 完成微积分、线性代数、概率论与数理统计以及任意一种编程语言。
Have read/taken some machine learning courses and books. 阅读过机器学习相关书籍。

How to join 如何加入

MLAPP reading perfectly fit the undergraduates and junior graduates.欢迎本科生和低年级研究生加入！
Seats are LIMITED and please contact Wenbo Hu for details. (Email: wenbohu[at]hfut.edu.cn) 名额有限，请联系胡文波老师。
You can also pay attention to the notice from counselors and teachers for the spring semester of 2024. 也可以请关注2024年春季学期辅导员老师的通知。

Mentors:

Wenbo Hu,
Richang Hong