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Description
This module focuses on applying advanced machine learning techniques to solve problems in the energy sector. The module is built around some of the most challenging energy-related problems, including:
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Short-term forecasting (load, price, renewables generation)听
Power systems operation听
Battery optimisation听
Remote sensing听
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These topics will be discussed in detail, covering the current academic literature and state of the art, providing you with the domain expertise required to choose and develop methods which are appropriate for the problem. The module covers the following topics in machine learning:
Computer vision models听
Time series modelling with deep learning
Reinforcement learning
Feature engineering
Model selection
Ensembling methods
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You will learn the skills necessary to deploy machine learning models in the real world. Module will cover methods for building pipelines to automate data cleaning, model selection, training, and deployment. In addition, you will cover the practical and computational considerations of implementing machine learning methods and how these can be addressed. The course will be taught in the Python programming language.
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
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