EDS 232

Course Name
Machine Learning in Environmental Science

Prerequisites
EDS 221 & EDS 222
Units
4
Description

Machine learning (ML) can help process big or complex data and extract knowledge. It forms one of the foundations in data science. This course provides a broad introduction to classic machine learning and statistical pattern recognition. Topics include supervised learning (decision trees, random forest, support vector machines, neural networks) and unsupervised learning (clustering, dimensionality reduction). Problems and exercises are framed within environmental science applications. The course will be taught using Python. 

 

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