MACHINE LEARNING|LOGISTIC REGRESSION|SUPPORT VECTOR MACHINES|DEEP LEARNING|UNSUPERVISED LEARNING

Aims:

To have a full understanding of the learning outcomes.

Learning outcomes:

On successful completion of the module, a student will be able...

Introduction to Machine Learning (COMP0088)

Aims:

To have a full understanding of the learning outcomes.Learning outcomes:

On successful completion of the module, a student will be able to:

Understand machine learning at both the theoretical and practical level;
	Solve real-world machine learning problems using the right tools.
Content:

The module will cover the following topics, the focus of which may be subject to change:

Introduction to Supervised Learning

Linear models for regression and classification: least squares, logistic regression.
	Concepts of overfitting and regularisation, L1 and L2 regularisation.
	Boosting, Decision Trees, Random Forests.
	Support Vector Machines.
	Deep Learning: Neural Networks for regression and classification, Convolutional Neural Networks, Recurrent Neural Networks.
Introduction to Unsupervised Learning

K-means, Principal Components Analysis, Embeddings & Representation Learning.
	Expectation-Maximisation, Mixture of Gaussians, Hidden Markov Models.
	Deep Autoencoders, Generative Adversarial Networks.
Requisites:

To be eligible to select this module as an optional or elective, a student must: (1) be registered on a programme and year of study for which it is formally available; (2) have an understanding of Calculus, Linear Algebra and Probability Theory; and (3) have proficiency in coding (preferably in Python).

PLANNING URBAN POLITICS ENVIRONMENTAL GOVERNANCE BEEBEEJAUN

This module enables students to situate planning within the wider political, environmental and social context in which it operates. We will set out key debates...

Urban and Environmental Politics (BPLN0084)

This module enables students to situate planning within the wider political, environmental and social context in which it operates. We will set out key debates attempting to explain and analyze urban and environmental political dynamics and their complex inter-relationships before exploring important contemporary challenges.

On successful completion of the module each student will:

Have gained a greater understanding of key urban and environmental theories and their relationship to cities and urban development
	Be more fully aware of the political context in which planning and related regulation operates
	Be able to critically analyse contemporary debates in urban and environmental politics
	Better understand the varied impacts that urban and environmental issues have on different communities and social groups