STATS 765 - Statistical Learning for Data Science
Faculty
Science
Department
Statistics
Points:
15
Available Semesters:
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Course Components
Labs
Tutorials
Lectures
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TBLs
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Description: Concepts of modern predictive modelling and machine learning such as loss functions, overfitting, generalisation, regularisation, sparsity. Techniques including regression, recursive partitioning, boosting, neural networks. Application to real data sets from a variety of sources, including data quality assessment, data preparation and reporting.
Prerequisites / Restrictions
Prerequisite: 15 points from ENGSCI 314, STATS 201, 207, 208 and 15 points from STATS 210, 225, 707 Corequisite: May be taken with STATS 707 Restriction: STATS 369
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