MLS: Machine Learning Systems

Course Contacts

Your lecturer for this course is 

• ML systems and general course organization: Luo Mai (luo.mai@ed.ac.uk)
• Data systems + coursework design / marking: Yang Cao (yang.cao@ed.ac.uk)

Course Introduction

The course on 'Machine Learning Systems' introduces the design of such systems and highlights their application in the hands-on experience of large-scale AI infrastructure. Students will acquire the skills necessary to analyse and implement (i) systems that retrieve large-scale data and (ii) systems that train and deploy large-scale machine learning models.

Learning Outcomes

On completion of this course, the student will be able to:

1. Understand different types of data, queries, workflows, and architectures of machine learning systems. Demonstrate the appropriate choice and use of particular data structures, and architectures.
2. Construct, analyse and profile implementation to given machine learning systems and iteratively improve the performance of those systems.
3. Compare and evaluate different systems and suggest/synthesise an appropriate system adoption solution.
4. Present the system solutions and engage in professional dialogue with peers to improve their solutions.
5. Reflect on the wider quality and security issues of data and machine learning models when discussing with specialist practitioners.

Course Schedule

Thursdays, 12:10–14:00, Lecture Theatre C, 40 George Square.