The seminar covers recent results in the increasingly important field of hardware acceleration for data science and machine learning, both in dedicated machines or in data centers.
Objective
The seminar aims at students interested in the system aspects of machine learning, who are willing to bridge the gap across traditional disciplines: machine learning, databases, systems, and computer architecture.
Content
The seminar is intended to cover recent results in the increasingly important field of hardware acceleration for data science and machine learning, both in dedicated machines or in data centers.
Prerequisites / Notice
The seminar should be of special interest to students intending to complete a master's thesis or a doctoral dissertation in related topics.
Performance assessment
Performance assessment information (valid until the course unit is held again)