Pythonic Machine Learning
We will code machine learning solutions for various datasets including Graphs, Images and Sequences. The emphasis will strongly be on developing robust code and other best practices.
讲师
日期
2025年02月25日 至 05月27日
位置
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| 周二 | 09:50 - 11:25 | A3-3-301 | ZOOM 05 | 293 812 9202 | BIMSA |
| 周二 | 13:30 - 15:05 | A3-3-301 | ZOOM 05 | 293 812 9202 | BIMSA |
修课要求
A background in statistics/mathematics/physics
课程大纲
1. Basic Python, Data types, File handling, Vectorization
2. Object Oriented Programming, Inheritance
3. Machine Learning an introductory dataset, evaluations and pitfalls
4. The underlying theory
5. Machine Learning with best practices (models, bias/variance, performance metrics, inference)
6. Unsupervised Learning
7. Machine Learning on Graphs
8. Deep Learning
2. Object Oriented Programming, Inheritance
3. Machine Learning an introductory dataset, evaluations and pitfalls
4. The underlying theory
5. Machine Learning with best practices (models, bias/variance, performance metrics, inference)
6. Unsupervised Learning
7. Machine Learning on Graphs
8. Deep Learning
听众
Advanced Undergraduate
, Graduate
, 博士后
视频公开
公开
笔记公开
公开
语言
英文
讲师介绍
Shailesh Lal于Harish Chandra研究所获得博士学位。他的研究兴趣是机器学习在弦理论和数学物理中的应用，弦理论中的黑洞和higher-spin holography。