Instructions:• Answer the following in question-and-answer format. • Each questi

Instructions:• Answer the following in question-and-answer format. • Each question should be answered in 260 to 300 words • References: At least one-two peer reviewed scholarly journal references are required per question. References should be added after completion of the question. 1. Compare and contrast predictive analytics with prescriptive and descriptive analytics. Use examples.2. Discuss the process that generates the power of AI and discuss the differences between machine learning and deep learning.3. Why are the original/raw data not readily usable by analytics tasks? What are the main data preprocessing steps? List and explain their importance in analytics.4. What are the privacy issues with data mining? Do you think they are substantiated?5. What is the relationship between Naïve Bayes and Bayesian networks? What is the process of developing a Bayesian networks model?6. List and briefly describe the nine-step process in con-ducting a neural network project.
Requirements: 260-300 words per question

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