Description
Introduction to Machine Learning and Big Data Analytics. Topics include: Association Rule Mining, Classification, Clustering, Linear and Logistic Regression, Distributed File System, Batch and Stream Data Processing, and other related. Applications on other domains such as multimedia, networks, finance, and/or business.
Prerequisites
- Prerequisite(s): IRM 3006 .
Conditions and arrangements
- Prerequisite(s): IRM 3006 .
- Lectures three hours a week.
Reference text in its original language
Introduction to Machine Learning and Big Data Analytics. Topics include: Association Rule Mining, Classification, Clustering, Linear and Logistic Regression, Distributed File System, Batch and Stream Data Processing, and other related. Applications on other domains such as multimedia, networks, finance, and/or business.
- Prerequisite(s): IRM 3006 .
- Lectures three hours a week.
Sources and references
Dates and sources are retained to help you verify the information. Translations are provided to facilitate reading; the official source governs conditions and requirements.
Source reference : https://calendar.carleton.ca/undergrad/courses/IRM/