"

买球APP软件

"
学校主页 加入收藏 English
当前位置: 首页 >> 通知公告 >> 正文 通知公告
Short Course: Statistical Machine Learning
来源:  点击次数: 次 发布时间:2022-05-26   编辑:统计与数学学院



Course outline
Data Science is an emerging and inherently interdisciplinary field, with Statistical Machine Learning techniques forming a key set of skills. This course will cover a wide range of popular supervised and unsupervised learning methods including regression, classification, deep learning, model selection and Bayesian computation. The course will also offer an insight into how these statistical methodologies are applied into business applications such as credit scoring and customer behavior analysis.

 

Lecturer: Associate Professor Minh-Ngoc Tran, University of Sydney Business School

Minh-Ngoc is with the Discipline of Business Analytics, University of Sydney Business School. He obtained a BSc and a MSc both in Mathematics from the Vietnam National University at Hanoi, and a PhD in Statistics in 2012 from the National University of Singapore. Minh-Ngoc’s main research interest is Bayesian computation and statistical Machine Learning with a special focus on Variational Bayes. He is also working on bringing state-of-the-art quantum computation techniques into data analysis. He is interested in promoting the use of modern Bayesian computation techniques in Cognitive Science, Consumer Behaviour and Financial Econometrics. Minh-Ngoc’s research has been published in many top-tier statistical journals and conferences. His research has been well funded with more than $4 million including four ARC grants. He is also an enthusiastic educator.

 

Prerequisites
This course is suitable for students who are interested in Data Science and have some background in statistics or related fields such as computer science, mathematics and econometrics. Also, some basic knowledge of programming is useful, as the practical part of the course will be delivered using the Python statistical software.

 

Register the course

Please scan this QR code to register. Registration is open till June 05, 24:00.

 

本课程受中央财经大学引智项目支持。


Schedule and contents

Day 1

June 8 Wednesday

Course: Statistical Machine Learning

08:00-11:30 Module 1: Introduction to Statistical Learning

1

Overview of the course

2

Introduction to Statistical Learning

3

Linear Regression 1: Simple Linear Regression

Lab 1

Introduction to Python

13:00-16:30 Module 2: Linear Regression

4

Linear Regression 2: Multiple Linear Regression

5

Linear Regression 3: Multiple Linear Regression

6

Linear Regression 4: Lasso, ridge and other regularizations

Lab 2

Introduction to Python

 

Day 2

June 9 Thursday  

Course: Statistical Machine Learning

08:00-11:30 Module 1: Classification

1

Classification 1: Introduction

2

Classification 2: kNN, logistic regression and advanced concepts

3

Classification 3: kNN, logistic regression and advanced concepts

Lab 1

Python for data analysis

13:00-16:30 Module 2 : Model selection

4

Model selection 1: Introduction

5

Model selection 2: Bias-variance decomposition

6

Model selection 3: Popular model selection methods

Lab 2

Python for data analysis

 

Day 3

June 15 Wednesday

Course: Statistical Machine Learning

08:00-11:30 Module 1: Deep learning

1

Deep Learning 1: Introduction

2

Deep Learning 2: Feedforward neural networks

3

Deep Learning 3: Feedforward neural networks

Lab 1

Linear regression with Python

13:00-16:30 Module 2 : Deep learning

4

Deep Learning 4: Backpropagation algorithm

5

Deep Learning 5: Recurrent neural networks

6

Deep Learning 6: Recurrent neural networks

Lab 2

Linear regression with Python

 

Day 4

June 16 Thursday

Course: Statistical Machine Learning

08:00-11:30 Module 1: Bayesian computation

1

Introduction to Bayesian statistics

2

Introduction to Bayesian statistics

3

Simple Monte Carlo methods

Lab 1

Deep learning with Python

13:00-16:30 Module 2 : Bayesian computation

4

Simple Monte Carlo methods

5

MCMC and Variational Bayes

6

MCMC and Variational Bayes

Lab 2

Deep learning with Python

 

首页

          版权所有:中央财经大学统计与数学学院  
          地址:北京市昌平区沙河高教园中央财经大学沙河校区1号学院楼   邮政编码:102206   电 话:(010)61776184    
          邮箱:samofcufe@cufe.edu.cn    
         

学院公众号

买球APP软件 "