STATS 765 - Statistical Learning for Data Science

Course Overview

test

Faculty

Science

Department

Statistics

Points:

15

Available Semesters:

{}

Course Components

Labs

Tutorials

Lectures

Exam

TBLs

Workshops

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

Average Rating From 0 Reviews

L

Teaching Quality

-

L

Content Quality

-

L

Workload

-

L

Difficulty

-

0% - Would Recommend

0% - Would Not Recommend

Reviews