Part 1: Complete the following assignment in one MS word document:
Chapter 5 –
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 questions :
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.
Internet exercise #7 (go to neuroshell.com click on the examples and look at the current examples listed, the Gee Whiz example is no longer on the page).
When submitting work, be sure to include an APA cover page and include at least two APA formatted references (and APA in-text citations) to support the work this week.
All work must be original (not copied from any source).
Create a discussion thread (with your name) and answer the following question:
Discussion (Chapter 5): What is the relationship between Naïve Bayes and Bayesian networks? What is the process of developing a Bayesian networks model?
Note: The first post should be made by Wednesday 11:59 p.m., EST. I am looking for active engagement in the discussion. Please engage early and often.
Your response should be 250-300 words. Respond to two postings provided by your classmates.
There must be at least one APA formatted reference (and APA in-text citation) to support the thoughts in the post. Do not use direct quotes, rather rephrase the author’s words and continue to use in-text citations.
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