线上讲座公告:Seminar on Data Science and Machine Learning

发布时间:2021-12-15浏览次数:104

Time: 2021/12/17 – 2021/12/21 10:00-11:30

 

Online Meeting ID: 腾讯会议536-8797-9214

点击链接入会:https://meeting.tencent.com/dm/BEXC3DmcdgJm

 

Talk 1: Tools for Data Science and Machine Learning (2021/12/17 10:00-11:30)

This talk is an Introduction to data science and machine learning. Major tasks in data science and machine learning, and tools for handling data will be briefly introduced. R, the most popular statistical software, will also be introduced.

 

Talk 2: Regression Methods for Machine Learning (2021/12/18 10:00-11:30)

In this talk, several regression methods for machine learning will be discussed. Potential topics include multiple linear regression and some Tree-based methods. Advantages and disadvantages for each model will be discussed.

 

Talk 3: Classification Methods for Machine Learning (2021/12/19 10:00-11:30)

In this talk, several classification methods for machine learning will be discussed. Potential topics include logistic regression, K-nearest neighbors, and support vector machine. Advantages and disadvantages for each model will be discussed.

 

Talk 4: Dimensionality Reduction and Clustering: How to better profile your data (2021/12/20 10:00-11:30)

This talk will focus on unsupervised learning methods, including principle component analysis, K-means clustering and hierarchical clustering. The challenge of unsupervised learning will be discussed and examples about the evaluation of unsupervised learning results will be demonstrated.

 

Talk 5: Data Visualization, Storytelling, and Effective Communication (2021/12/21 10:00-11:30)

This talk will focus on how to effectively communicate the analysis results obtained using data science and machine learning. Popular packages in R will be demonstrated using examples.

 

About the Lecturer:

Dr. Wenshuang Wang received her Ph.D. in Mathematical Sciences from Mississippi State University. Dr. Wang is currently an assistant professor of data science at the department of mathematics at the University of Houston (UH). Prior to joining UH, Dr. Wang was a statistician at the Texas medical center in the Great Houston Area. Dr. Wang’s research interest includes Data Science in Healthcare and Energy for better decision making and quality improvement.


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