7088CEM Assignment Help
Artificial Neural Networks Assignment help
• You can use any ANN that you like, whether it was covered in the module or not. However,
• Your work must be strictly related to ANN. No other machine learning methods are accepted.
• The dataset you use must be publicly available, e.g., in Kaggle, UCI, or other open repositories:
1. UCI: http://archive.ics.uci.edu/ml
2. Kaggle: https://www.kaggle.com/datasets
• Everything you do should be reproducible: The link to the dataset should be provided (direct link to the dataset itself not the site where it is hosted). The code used, in its totality, should be included as text (not image, file, link, etc.) in the appendix. If you use a code that is not yours, whether totally or partially, this must be clearly indicated. Please do upload the executable code on “GitHub” and provide the link. Ensure the repository is set to public so can be accessed.
• You should provide in the appendix clear evidence, using screen captures, that you installed the software and ran every part of the experiments. The screen captures should also clearly show the device (i.e., user ID) on which the experiments were conducted/the software was installed.
• Except for the dataset, NO LINKS of any kind to your work are allowed. Everything should be included in the report itself (the body or the appendix)
• Plagiarism and collusion are taken extremely seriously. Any part, from any source, of any type, in any language, should be COMPLETELY AND CLEARLY cited. If you use a figure/table/image that is not yours, the source should be cited in the caption.
Organisation of the report and marking scheme:
o Cover page: the title of the project
o Section 1. Introduction (5 marks)
Should include the description of the chosen real-life problem and its significance (1-2 pages)
o Section 2. Related work (10 marks)
Should explain and properly cite the (most notable) works already done related to the selected problem. The references need to be from journal papers not just from websites.
o Section 3. Dataset (10 marks)
Should include the description of the publicly available dataset and its link (1-3 pages). Please describe the processes you use to clean and formalize the data set for your use.
Section 4. Method(s) (15 marks)
Should describe the appropriate neural network(s), together with the learning algorithm(s) and other parameters, tried to solve the problem. Please provide the reasoning behind selecting the type of the neural network and parameters.
o Section 5. Experimental results (15 marks)
Should explain the rigor experiments conducted and compare their detailed results.
o Section 6. Discussion and future work (5 marks)
Should present the summary of the findings (1-2 pages). Also provide what future work can be conduced on this project.
o References (5 marks)
List of references cited in the other sections, in the APA style
o Appendix1- Screenshots and steps (15 marks)
Should contain the screenshots of all the steps together with brief descriptions such that an interested reader can re-do all the experiments in this research.