Q1. evaluate the history of the Data Encryption Standard (DES)

Q1. evaluate the history of the Data Encryption Standard (DES) and then how it has transformed cryptography with the advancement of triple DES. You must use at least one scholarly resource.  Every discussion posting must be properly APA formatted. (250 to 300 words)

Q2. What is the relationship between Naïve Bayes and Bayesian networks? What is the process of developing a Bayesian networks model?Your response should be 250-300 words.  There must be at least one APA formatted reference (and APA in-text citation) to support the thoughts in the post.  Do not use direct quotes, rather rephrase the author’s words and continue to use in-text citations.

Q3.List and briefly describe the nine-step process in con-ducting a neural network project.Your response should be 250-300 words. There must be at least one APA formatted reference (and APA in-text citation) to support the thoughts in the post.  Do not use direct quotes, rather rephrase the author’s words and continue to use in-text citations.

Q4. Complete the following assignment in one MS word document and include at least two APA formatted references (and APA in-text citations) to support the work this week. (Each below question 150 words)

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.

5.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.

6.What is deep learning? What can deep learning do that traditional machine-learning methods cannot?

7.List and briefly explain different learning paradigms/ methods in AI.

8.What is representation learning, and how does it relate to machine learning and deep learning? 

9.List and briefly describe the most commonly used ANN activation functions.

10. What is MLP, and how does it work? Explain the function of summation and activation weights in MLP-type ANN.

11. Cognitive computing has be come 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.

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