Data Management and Machine Learning

CS 8803 DMM: Data Management and Machine Learning (Fall 2019)

Announcements:

No classes on 09/02, 10/14 and 11/27 due to Labor Day Break, Fall Recess and Thanksgiving respectively.
Major course announcements will be made available here and on GT Canvas
Lecture slides have been uploaded to Files section on Canvas
Include your preferred teammates for paper presentation in your "paper preference" email. We will try to accomodate that. Otherwise, students who express their interests in same paper will be asked to form a presentation group. Note that paper presentation group can be different from Project group.

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:

Utilizing machine learning technologies to solve hard data management challenges, such as data cleaning
Utilizing data management technologies to solve hard machine learning challenges, such as model interpretation, debugging, and feature engineering.

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.

Instructor: Xu Chu

Email: xu.chu@cc.gatech.edu
Office: Klauss 3322

TA: Aman Shishodia

Email: aman.shishodia@gatech.edu

Time: Mon and Wed, 3:00 - 4:15pm
Location: College of Computing 102
Office Hours: 3:30-4.30pm every Tue starting from Aug 20th
Appointments: E-mail me to book a slot. The subject of the email should be "CS 8803".

Prerequisites

Students should have basic understandings of data analytics and machine learning. Though not required, an undergraduate course in relational database systems and an undergraduate course in machine learning would be helpful. References provide some relevant courses and materials.