Data Management Challenges in Machine Learning (Fall 2018)

Motivation

Big data processing poses many challenges, which are often characterized by the three V's (volume, velocity, and varity). 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 divided into two parts.

  1. Utilizing machine learning technologies to solve hard data management challenges, such as data cleaning
  2. Utilizing data management technologies to solve hard machine learning challenges, such as data representation and training data curation

Objectives

Students should gain a much deeper understanding of modern challenges in both data management and machine learning.

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 good research talk, and how to ask questions during a talk?

Logistics

Pre-requisites

Grading (Subject to change)

Schedule

TBD

References

 


  © Xu Chu 2018