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Posted: September 1st, 2023

Please write each answer 125 words for each question. Total 8 questions (Any 4 questions for Chapter 5 any 4 questions for chapter 6)

I need support with this Artificial Intelligence question so I can learn better.

Complete the following End-of-Chapter questions and submit as a single 12-font, single spaced MS WORD document. Do not include a cover page or table-of-content.

The question # MUST proceed your answer to each question (i.e. Exercise #1)

Chapter 5 – Discussion question #1, #2, #3, & #4 and
Exercise #6 and
Internet Exercise #7 (go to neuroshell.com click on the examples and look at the current examples. The Gee Whiz example is no longer on the page.)

Discussion

What is an artificial neural network and for what types of problems can it be used?
Compare artificial and biological neural networks. What aspects of biological networks are not mimicked by arti- ficial ones? What aspects are similar?
What are the most common ANN architectures? For what types of problems can they be used?
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 com- monalities and differences among their findings and prepare a report to summarize your understanding.

Chapter 6 – Discussion question #1, #2, #3, #4, & #5 and
Exercise 4

What is deep learning? What can deep learning do that traditional machine-learning methods cannot?
List and briefly explain different learning paradigms/ methods in AI.
What is representation learning, and how does it relate to machine learning and deep learning?
List and briefly describe the most commonly used ANN activation functions.
What is MLP, and how does it work? Explain the function of summation and activation weights in MLP-type ANN.Exercise#4 Cognitive computing has become a popular term to define and characterize the extent of the ability of machines/ computers to show “intelligent” behavior. Thanks to IBM Watson and its success on Jeopardy!, cognitive computing and cognitive analytics are now part of many real- world intelligent systems. In this exercise, identify at least three application cases where cognitive computing was used to solve complex real-world problems. Summarize your findings in a professionally organized report.
Citations and references plz, no plagiarism.

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