IDA Wiki

Lecture Big Data: Scalable Machine Learning

General Information

Lecture

Thursdays 12-14

Room

MAR 4.065

Teachers

Mikio L. Braun

Contact

mikio.braun@tu-berlin.de

Course Information (ISIS)

https://isis.tu-berlin.de/course/view.php?id=4643

Introduction

In this lecture series, we will discuss how large scale learning is performed. Individual algorithms will be studied, and shown how learning algorithms are modified in order to be able to deal with large data sets. These approaches don't necessarily lead to scalable computations in the sense of distributed systems, but more often rely on skillfull approximations and simplifcations which nevertheless ensure that the resulting algorithm leads to good predictions.

Topics include:

Prerequisites

This is an advanced course which assumes working knowledge of machine learning algorithms as provided by the lectures Machine Learning 1 and/or Machine Learning 2. Apart from that, working knowledge of linear algebra, multivariate analysis, probability theory, as well as computing architectures.

IDA Wiki: Main/SS15_VLBigData (last edited 2015-04-16 07:40:07 by MikioBraun)