The University of Sheffield
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COM6012   Scalable Machine Learning   (15 credits)

 
Year Running: 2017/2018
Credit level: F7

Description

This module will focus on technologies and algorithms that can be applied to data at a very large scale (e.g. population level). From a theoretical perspective it will focus on parallelisation of algorithms and algorithmic approaches such as stochastic gradient descent. There will also be a significant practical element to the module that will focus on approaches to deploying scalable ML in practice such as SPARK, programming languages such as Python/Scala and deployment on high performance computing platforms/clusters.

 

Reading List


Please click here for reading list.
 

Teaching Methods

Delivery Type Hours
Independent 114.0
Lecture 10.0
Problem Solving 16.0
Seminar 10.0
 

Methods of assessment

Assessment Type Duration % of formal assessment Semester
Course Work 0.0 40 % S2
Exam 2.0 60 % S2
 

Teaching methods and assessment displayed on this page are indicative for 2017-18.