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Unit of study_

Machine Learning for Business - QBUS6850

Year - 2018

Machine Learning is a fundamental aspect of data analytics that automates analytical model building in modern business. In the big data era, managers are able to use very large and rich data sources and to make business decision based on quantitative data analysis. Machine Learning covers a range of state-of-the-art methods/algorithms that iteratively learn from data, allowing computers to find hidden patterns and relationships in such data so as to support business decision. This unit introduces modern machine learning techniques and builds skills in using data for everyday business decision making. Topics include: Machine Learning Foundation; Modern Regression Methods; Advanced Classification Techniques; Latent Variable Models; Support Vector Machines (SVM) and Kernel Methods; Artificial Neural Networks; Deep Learning; and Machine Learning for Big Data. Emphasis is placed on applications involving the analysis of business data. Students will practise applying machine learning algorithms to real world datasets by using an appropriate computing package.

1x 2hr lecture per week (13 weeks) and 1x 1hr tutorial (lab) per week (12 weeks)

assignment 1 (10%); assignment 2 (10%); group project (20%); mid-semester exam (20%); final exam (40%)




Faculty: Business (Business School)

Semester 2

30 Jul 2018

Department/School: Business Analytics
Study Mode: Normal (lecture/lab/tutorial) day
Census Date: 31 Aug 2018
Unit of study level: Postgraduate
Credit points: 6.0
EFTSL: 0.125
Available for study abroad and exchange: No
Faculty/department permission required? No
Courses that offer this unit

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