I’m working on a computer science question and need an explanation to help me understand better.
1)What is the relationship between Naïve Bayes and Bayesian networks? What is the process of developing a Bayesian networks model? 500 plus words
other questions no ccount
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.
6. Go to neoxi.com. Identify at least two software tools
that have not been mentioned in this chapter. Visit Web
sites of those tools and prepare a brief report on their
capabilities.
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.
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