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Artificial Neural network and Deep learning

Artificial Neural network and Deep learning

Artificial Neural network and Deep learning

Chapter 5

Discussion Question 1: What is an artificial neural network and for what type of problem can it be used for?

Discussion Question 2: Compare artificial and biological neural networks. What aspect of biological networks are not mimicked by artificial ones? What aspects are similar?

Discussion Question 3: What are the most common ANN architectures? For what types of problem can they be used?

Discussion Question 4: ANN can be used 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 commonalities and differences among their findings and prepare a report to summarize your understanding.

Internet Exercise 7: Go to http://www.neuroshell.com/examples.html. Look at USG Corporation example. Comment on the feasibility of achieving the results claimed by the developers of this neural network model.

Chapter 6 

Discussion Question 1: What is deep learning? What can deep learning do that traditional machine-learning methods cannot?

Discussion Question 2: List and briefly explain different learning paradigms/methods of AI.

Discussion Question 3: What is representation learning, and how does it relate to machine learning and deep learning?

Discussion Question 4: List and briefly describe the most commonly used ANN activation functions.

Discussion Question 5: 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 resolve complex real-world problems. Summarize your findings in a professional organized report.

Textbook: Business Intelligence and Analytics 

ISBN: 9780135192016

Your response should be 5-6 pages. There must be APA formatted references (and APA in-text citation) to support the thoughts in the post.


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