Using the guidelines provided in this week's chapter (and other resources as needed), create a step-by-step IT security policy for handling user accounts/rights for a student who is leaving prematurely (drops, is expelled, and so on). You will need to consider specialized student scenarios, such as a student who works as an assistant to a faculty member or as a lab assistant in a computer lab and may have access to resources most students do not. Write your answer using a WORD document. Do your own work. Submit here. Note your Safe Assign score. Score must be less than 25 for full credit. You have three attempts. Using the guidelines provided in this week's chapter (and other resources as needed), create a step-by-step IT security policy for handling user accounts/rights for a student who is leaving prematurely (drops, is expelled, and so on). You will need to consider specialized student scenarios, such as a student who works as an assistant to a faculty member or as a lab assistant in a computer lab and may have access to resources most students do not. Write your answer using a WORD document. Do your own work. Submit here. Note your Safe Assign score. Score must be less than 25 for full credit. You have three attempts.

What are some of the difference between demand influences and supply influences on our pricing decisions? After reviewing this week’s resources and your research, consider the challenges marketers face as they seek to balance supply and demand. Increased prices typically result in lower demand and vice versa. However, this is not always the case. Identify a product in which a price increase or decrease resulted in the opposite demand and explain the factors why. What are some of the difference between demand influences and supply influences on our pricing decisions? After reviewing this week’s resources and your research, consider the challenges marketers face as they seek to balance supply and demand. Increased prices typically result in lower demand and vice versa. However, this is not always the case. Identify a product in which a price increase or decrease resulted in the opposite demand and explain the factors why.

MNIST / Fashion MNIST image data The main objective is to write a fully executed R-Markdown program performing dimension reduction on a high dimensional image data using MNIST (digits) and Fashion MNIST (apparel) images that are 28 x 28 pixels resolution. Make sure to describe the final hyperparameter settings of all algorithms that were used for comparison purposes. MNIST / Fashion MNIST image data The main objective is to write a fully executed R-Markdown program performing dimension reduction on a high dimensional image data using MNIST (digits) and Fashion MNIST (apparel) images that are 28 x 28 pixels resolution. Make sure to describe the final hyperparameter settings of all algorithms that were used for comparison purposes.

Describe various predictive ensemble methods and a business use of such methods. Describe various predictive ensemble methods and a business use of such methods.

Write a fully executed R-Markdown program and submit a pdf file solving and answering questions listed below under Problems at the end of chapter 13. For clarity, make sure to give an appropriate title to each section. Write a fully executed R-Markdown program and submit a pdf file solving and answering questions listed below under Problems at the end of chapter 13. For clarity, make sure to give an appropriate title to each section.

Dimension reduction techniques Describe in detail the difference between PCA, t-SNE and UMAP dimension reduction techniques. Dimension reduction techniques Describe in detail the difference between PCA, t-SNE and UMAP dimension reduction techniques.

Write at least 500 words discussing how text mining and anti-crime applications are making internet crime prevention easier. Write at least 500 words discussing how text mining and anti-crime applications are making internet crime prevention easier.

1. Show stacked bar charts of the most common terms within each of 2 topics from the Associated Press articles in the topicmodels package. Color the charts by topic. Comment your code line by line. 2. Show a stacked bar chart showing the words that have a Beta greater than 1/1000 in at least one topic with the greatest difference in Beta between topic 1 and topic 2. comment each line of your code. Submit one document with screenshots of your work in R Studio. Include a slice of your desktop with your screenshots. 1. Show stacked bar charts of the most common terms within each of 2 topics from the Associated Press articles in the topicmodels package. Color the charts by topic. Comment your code line by line. 2. Show a stacked bar chart showing the words that have a Beta greater than 1/1000 in at least one topic with the greatest difference in Beta between topic 1 and topic 2. comment each line of your code. Submit one document with screenshots of your work in R Studio. Include a slice of your desktop with your screenshots.

Write at least 500 words comparing and contrasting multi-threading and parallel processing. Write at least 500 words comparing and contrasting multi-threading and parallel processing.

1. What is the number of clusters recommended to create to utilize multiple cores without putting excessive pressure on other processes or applications? 2. How can you determine how many cores your cpu has? 3. Provide three examples of methods which R can process using GPU rather then CPU processors. 4. What does the data.table() function provide to big data processing? 5. What can one do with dcast.data.tale()? Submit one document with your answers and any screenshots of your work in R Studio. Include a slice of your desktop with your screenshots. 1. What is the number of clusters recommended to create to utilize multiple cores without putting excessive pressure on other processes or applications? 2. How can you determine how many cores your cpu has? 3. Provide three examples of methods which R can process using GPU rather then CPU processors. 4. What does the data.table() function provide to big data processing? 5. What can one do with dcast.data.tale()? Submit one document with your answers and any screenshots of your work in R Studio. Include a slice of your desktop with your screenshots.