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1. 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 com- monalities and differences among their findings and prepare a report to summarize your understanding.
2. What is an artificial neural network and for what types of problems can it be used?
3. Compare artificial and biological neural networks. What aspects of biological networks are not mimicked by arti- ficial ones? What aspects are similar?
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4. What are the most common ANN architectures? For what types of problems can they be used?
5. ANN can be used for both supervised and unsupervised learning. Explain how they learn in a supervised mode and in an unsupervised mode
question 1 is limit to 1-2 pages. questions from 2-5 can be on 2 pages. all 6 question should be in one doc with APA formatting.
Machine learning methods have been applied in various fields, such as solving problem domains in healthcare. Hence, with these methods, they predict risk factors through flexible techniques and algorithms, thus informing experts on areas that need improvement. Various studies have been conducted, which compare the applicability of multiple machine-learning methods. For instance, there is deep learning, which involves the use of artificial neuron networks. Other learning models incorporate different algorithms like support vector machines (SVM) or networks, Bayesian networks, K-nearest neighbors (kNN), random forests (RF), among others.(1420words)