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Task – Hyper-parameter Optimisation
In assignment 1 you created a feedforward artificial neural network (ANN) to solve a binary
classification task on tabular, numeric data. In this assignment we will expand upon these
concepts, and solve a classification task on a harder problem involving image input (See
Dataset section below).
In this assignment, you will be expected to research techniques of your own accord,
potentially beyond those that are taught within the module. This may involve state-of-the-art
techniques in machine learning.
You are expected to come up with a methodical and scientific approach to creating a model
for solving multi-class classification of images, incorporating many of the techniques within
the module such as different types of network, various architecture choices, hyper-parameter
optimisation techniques, dimensionality reduction methods, etc.
All of this will be written into a report outlining your project, comparing results, and evaluating
your experiments. At the end of this report you will conclude your findings, and discuss
considerations for these technologies towards the theme of ethical use of AI and how these
systems may be both beneficial and/or disruptive; specifically in the context of the proposed
solution for the CIFAR-10 dataset challenge and its potential applications.
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