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oThis assignment is worth 15% of the total mark for COMP338

oStudents will do the assignment individually.

Submission Instructions

oSend all solutions as a single PDF document containing your answers, results, and discussion of the results. Attach the source code for the programming problems as separate files.

oEach student will make a single submission to the Canvas system.

oThe deadline for this assignment 09/12/2022, 5:00pm

oPenalties for late submission apply in accordance with departmental policy as set out in the student handbook, which can be found at
http://intranet.csc.liv.ac.uk/student/msc-handbook.pdf and the University Code of Practice on Assessment, found at
https://www.liverpool.ac.uk/media/livacuk/tqsd/code-of-practice-on- assessment/code_of_practice_on_assessment.pdf

Image Classification with CNN

In this project, we will do image classification using the Fashion MNIST dataset. The lab “COMP338_Lab_08_Fashion_MNIST_Classification.ipynb” on Canvas shows the example source code for this assignment.

Tasks:
1.(30 marks) Design a deep neural network for image classification.
2.(30 marks) Train and test your network on Fashion MNIST dataset.
3.(40 marks) Write a report to clearly explain your network, the intuition behind your design, and discussion of your results.

Rules:
-You can refer to any papers and reuse any source code. However, you should clearly cite the references in your report.
-Use free Google Colab account (https://colab.research.google.com/) for training. The maximum training time on a free Google Colab account is 12 hours.

Our solution will be evaluated by:
-The robustness of your network design (30%).
-The accuracy of your trained model, compared with other students (30%).
-The completeness of your report (40%).