Courses / Module

Toggle Print

Module MACHINE LEARNING & NEURAL NETWORKS

Module code: CS401
Credits: 5
Semester: 1
Department: COMPUTER SCIENCE
International: Yes
Overview Overview
 

Machine learning principles; The probabilistic perspective on machine learning; Supervised, unsupervised, and reinforcement learning; Biological neurons and their relation to linear classifiers; Supervised learning techniques: linear regression, the perceptron learning rule, backprogation, recurrent networks, deep learning, support vector machines; Unsupervised techniques: k-means clustering, EM of gaussian mixtures, hidden markov models; Reinforcement learning: Policy-value iteration, Q-learning, TD-learning, deep reinforcement learning systems.

Open Learning Outcomes
 
Open Teaching & Learning methods
 
Open Assessment
 
Open Repeat options
 
Open Timetable
 
Back to top Powered by MDAL Framework © 2019
V5.2.0 - Powered by MDAL Framework © 2019