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Part1: 1) What is the relationship between Naïve Bayes and Bayesian networks? Wh

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Part1:
1) What is the relationship between Naïve Bayes and Bayesian networks? What is the process of developing a Bayesian networks model? 
Min 225 words
Part2:
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 arti- ficial 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.
Min 150 words required for each question 
Checklist:
APA Formatting
Part1 and Part2 needs to attached as two separate docs
Minimum of 2 references for each part. Please cite all the sources along with in text citations.
Plagiarism report

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