CS 8803 DML: Data Management and Machine Learning (Fall 2018)



Announcements:

Motivation

Big data processing poses many challenges, which are often characterized by the three V's (volume, velocity, and variety). On the other hand, machine learning is increasingly used by all kinds of data-driven applications. This course explores the interactions between these two exciting fields. This blogpost provides one perspective of such interactions.

Topics

Because of the purpose above, the course will be covered topics broadly categorized as follows:

Objectives

The course covers a wide range of moder challenges and sub-topics in both data management and machine learning. The students will get familiar with these sub-topics, and gain a deep understanding of one sub-topic by doing presentations and course projects.

Furthermore, since this is a graduate seminar, another important objective is to train students to master basic skills for being a researcher. The course will create a number of opportunities for students to learn how to read a paper, how to write a paper review, how to give a research talk, and how to write a research paper.

Logistics

We will be using Canvas for course announcements, uploading materials that should not be made public, and student discussions such as forming project groups.

Prerequisites

Academic Honesty:

Grading

References

 


  © Xu Chu 2018