Please submit the opening and closing paragraphs in color, here as ONE document. 

For the Introduction paragraph:

Green for first sentence (The grabber).

Blue for Transition sentences.

Purple for last Thesis Statement.

For the Conclusion paragraph:

Purple for the first Thesis restated sentence.

Blue for transition sentences.

Green for last sentence (Final grabber).

Introduction end with thesis statement and i opening sentence of the introduction we should include 

a surprising, disturbing, little-known, or wonderful fact, in text citation, and statistics, conclusions should be reverse of introduction 

Topics 

1. The Impact of Social Media on Brand Reputation in Retail Industry

2.Protecting Online Privacy for Individuals

3. Artificial Intelligence Fairness and Bias in Automated Decision-Making Systems

4. Succession Planning and Development of Leadership

5. E-Waste Management in the Tech Industry

6. Air Pollution and its Impact on Heart Disease

I have attached a pdf of the question. You are to do this project on linux in C++. In the end you will provide me with a zip file containing the required cpp and hpp files. Please try to create a makeFile so its easy for me to compile your code.

Today’s challenge is what to do with all of the data that has been created as a result of the Internet. The field of data science is trying to store, manage, classify and provide meaningful access to it. Think like a futurist. Create a report on where the field is going. Some points you might want to include are:

> What is Big Data? Why is it important? Where does Big Data come from?

> What do you believe the future of Big Data will be? Will it lose its popularity to something else? If so, what will it be?

> What is Big Data analytics? How does it differ from regular analytics?

> What are the critical success factors for Big Data analytics?

> What are the big challenges that one should be mindful of when considering implementation of Big Data analytics?

> What are the common business problems addressed by Big Data analytics?

> In the era of Big Data, are we about to witness the end of data warehousing? Why?

> What are the use cases for Big Data/Hadoop and data warehousing/RDBMS?

> What is stream analytics? How does it differ from regular analytics?

> What are the major uses of IoT?

> Why is the IoT considered a disruptive technology?

> The IoT has a growing impact on business and e-commerce. Find evidence.

Need 12-14 pages in APA format with introduction and conclusion. Must include minimum of 8 peer-reviewed citations.

ch-7

Disney is grossing more over time because the p-value is positive. Disney is grossing less over time because the p-value is positive. Disney is grossing more over time because the p-value is negative. Disney is grossing less over time because the p-value is negative. Disney is grossing more over time because the coefficient is positive. Disney is grossing less over time because the coefficient is positive. Disney is grossing more over time because the coefficient is negative. Disney is grossing less over time because the coefficient is negative. Bookmark question for later Can we rely on these results and expect to see something similar as new movies are added? Bookmark question for later Fill in all missing values of mpaa_rating with the value “Empty” Create dummy code features to convert mpaa_rating to sets of numeric 0/1 features for all values except “Empty” Run another MLR a few rows below the previous one using both days_since_release and all of the dummy codes you just created for mpaa_rating What did the inclusion of these dummy coded mpaa_rating features do to the model fit? Options: 1There is no way to tell from these results 2It made the model fit better 3Did not change it at all 4It made the model fit worse 17)Upload the Excel file containing the data and all of your regression models 7,17questions and read the instructions for both questions in assignment document.

ch-9 

 Chapter 9 Assignment. Here is the Instruction: Follow all the tasks shown in the video clips in Ch 9 and do them yourself while watching the clips. At the End, Turn in the File that You Produce While Watching the Author’s Demonstration. 

ch-10

Chapter 10 Assignment. Here is the Instruction: Follow all the tasks shown in the video clips in Ch 10 and do them yourself while watching the clips. At the End, Turn in the File that You Produce While Watching the Author’s Demonstration. 

ch-7.2

 Chapter 7 Logistic Regression Assignment. Submit R File for Codes and Word Document with Your Analysis. 

ch-11

 11.6 ML Studio: Algorithm Selection (football and airline) Background You are a data scientist for a major airline that has been collecting customer satisfaction surveys from random customers. You are hoping to better understand what causes your customers to be loyal and come back to your airline whenever they need a flight. Data Use the two csv files below to complete the tasks. airline_satisfaction.csv Dataset details: https://www.kaggle.com/datasets/teejmahal20/airline-passenger-satisfaction nfl_plays_2022.csv Dataset found at: http://www.nflsavant.com/about.php This may is the same dataset used in the feature selection assessment. You do not need to reupload it into ML Studio if you already did so. Task Complete the tasks found in the question details below Download and use the template file provided to track your models and upload it where directed Publish your completed experiment to the AI Gallery and paste the URL where directed 10)Publish your experiment to the AI Gallery and copy/paste the URL below 11)Upload the Excel file template you used to record all of your modeling results.

In this project deliverable, you should develop the 10 functionalities proposed in deliverable 2 in MS Access, and turn in the following files:

1) The updated project proposal (Word document) which has the same five sections as before. Copy my comments from the deliverable 2 and highlight any changes you made from the previous version by turning track changes on in MS Word (or using a different text color). 

2) A MS Visio file that contains the updated ERD (even if you didn’t make any changes from the previous version). 

3) An Access database should have all the tables shown in the ERD with at least 6 to 7 records in each table and all the PK/FKs/relationships/data types properly enforced. The referential integrity option should be checked when setting up the relationship in MS Access. The Access file should also include the 10 queries used to accomplish the 10 functionalities outlined in the proposal. Name the 10 queries based on the order of functionalities listed in the Word document. 

Please name the above file as Project_3_Lastname.docx /.vsdx /.mdb, respectively). All group members need to submit the these three project files.

The final project deliverable is due on November 30 at 11:59 PM. This is a firm deadline and no extension will be given. You are strongly encouraged to submit your project files earlier to avoid any technical issues.