Answer the below questions as instructed. Kindly read the instructions properly before you answer
1. What is an artificial neural network and for what types of problems can it be used?
2. Compare artificial and biological neural networks. What aspects of biological networks are not mimicked by artificial
ones? What aspects are similar?
3. What are the most common ANN architectures? For what types of problems can they be used?
4. ANN can be used for both supervised and unsupervised learning. Explain how they learn in a supervised mode
and in an unsupervised mode.
Exercise 6: Go to Google Scholar (scholar.google.com). Conduct a search to find two papers written in the last five years that compare and contrast multiple machine-learning methods for a given problem domain. Observe commonalities and differences among their findings and prepare a report to summarize your understanding. (Must be 1 full page) You must specify which 2 papers you considered: so paper full names must be added.
Exercise 7: Go to neuroshell.com. Look at Gee Whiz examples. Comment on the feasibility of achieving the results claimed by the developers of this neural network model. (Must be 1 full page)
For 1-4 questions, there is no page restrictions: you can answer accordingly but each question that is answered should have the in-text citation and an APA reference in the Reference Page (No websites/wiki/ending with .com references are considered as Peer Reviewed)
Exercise 6 & 7 must be each 1 full page i.e., 2 pages of content (should have the in-text citation and an APA reference in the Reference Page – No websites/wiki/ending with .com references are considered as Peer Reviewed)
APA Format
No plagiarism
In-text Citations Mandatory
No Spinbot/Synonymic words please
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