7135CEM – Modelling and Optimization Under Uncertainty - Computer Science Assignment Help

Assignment Task

Module Learning Outcomes Assessed:

On completion of this module the student should be able to:

1. Apply supervised and unsupervised learning applications using Gaussian process emulators.
2. Apply Dirichlet processes for unsupervised learning applications
3. Develop the knowledge and skills necessary to design, implement and apply the Graphical models to solve real world applications.
4. Evaluate the applications of fuzzy systems and their usage in hybrid intelligent systems, in combination with evolutionary computing and other machine learning methods.
5. Apply evolutionary computing methods to develop solutions for the real world optimisation problems and appraise their advantages and limitations.

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