SOLUTION! ITS-839 Course Paper, a total of 25 points (25% of the total course points) Sean Weatherspoon GuidelinesRubrics to deliver Course Paper · Submit the final paper, no later than August 6 · Make sure yo

Article Writing

ITS-839 Course Paper, a total of 25 points (25% of the total course points)

Haven’t Found The Relevant Content? Hire a Subject Expert to Help You With
SOLUTION! ITS-839 Course Paper, a total of 25 points (25% of the total course points) Sean Weatherspoon GuidelinesRubrics to deliver Course Paper · Submit the final paper, no later than August 6 · Make sure yo
Post Your Own Question And Get A Custom Answer
Hire Writer

Sean Weatherspoon

GuidelinesRubrics to deliver Course Paper

· Submit the final paper, no later than August 6

· Make sure you include the major 7 sections graded mentioned below in your paper

· The deliverable should contain the following components:

(1) Overall Goals/Research Hypothesis (10 %)

1-3 research questions to navigate/direct all your project.

· You may delay this section until (1) you study all previous work and (2) you do some analysis and understand the dataset/project

(2) (Previous/Related Contributions) (15 %)

As most of the selected projects use public datasets, no doubt there are different attempts/projects to analyze those datasets. 30 % of this deliverable is in your overall assessment of previous data analysis efforts. This effort should include:

· Evaluating existing source codes that they have (e.g. in Kernels and discussion sections) or any other refence. Make sure you try those codes and show their results

· In addition to the code, summarize most relevant literature or efforts to analyze the same dataset you have picked. 

· For the few who picked their own datasets, you are still expecting to do your literature survey in this section on what is most relevant to your data/idea/area and summarize those most relevant contributions.

(3) A comparison study (15 %)

Compare results in your own work/project with results from previous or other contributions (data and analysis comparison not literature review)

The difference between section 3 and section 2 is that section 2 focuses on code/data analysis found in sources such as Kaggle, github, etc. while section 3 focuses on research papers that not necessary studied the same dataset, but the same focus area

(4) Preprocessing activities, Features Selection / Engineering (10 %)

(See this link for content of the next section)

https:// What were the most important features?

· We suggest you provide:

· a variable importance plot (an example here about halfway down the page), showing the 10-20 most important features and

· partial plots for the 3-5 most important features

· If this is not possible, you should provide a list of the most important features.

· How did you select features?

· Did you make any important feature transformations?

· Did you find any interesting interactions between features?

· Did you use external data? (if permitted)

(5) Training Method(s) 10 %

· What training methods did you use?

· Did you ensemble the models?

· If you did ensemble, how did you weight the different models?

A6. Interesting findings

· What was the most important trick you used?

· What do you think set you apart from others in the competition?

· Did you find any interesting relationships in the data that don’t fit in the sections above?

Many customers are happy to trade off model performance for simplicity. With this in mind:

· Is there a subset of features that would get 90-95% of your final performance? Which features? *

· What model that was most important? *

· What would the simplified model score?

· * Try and restrict your simple model to fewer than 10 features and one training method.

 (6) Accuracy metrics reporting, charts, Model Execution Time (10 %)

Many customers care about how long the winning models take to train and generate predictions:

· How long does it take to train your model?

· How long does it take to generate predictions using your model?

· How long does it take to train the simplified model (referenced in section A6)?

· How long does it take to generate predictions from the simplified model?

(7) Use of ensemble methods (15 %)

Per the last chapter we have, make sure you employ at least two different ensemble models in your code and show the model details and results


Citations to references, websites, blog posts, and external sources of information where appropriate.


Summarize the most important aspects of your model and analysis, such as:

The training method(s) you used (Convolutional Neural Network, XGBoost)

The most important features

The tool(s) you used

How long it takes to train your model



Quality Criteria (10-20% of overall project):

1. Thorough performance analysis: Results in data analysis can be misleading. Without detail analysis of different performance metrics (e.g. accuracy, recall, ROC, AUC, etc.) one-side view of results can present incomplete and inaccurate findings. Presenting a thorough analysis for overall performance of your models will show that you did not ignore any factor in your model. 

2. Following standard project templates: You can find through the Internet several standard templates for data science projects (How to structure your code, data, etc.). While following standard templates is not a must or required but will be considered as part of quality criteria. Here are examples of code templates for different programming environments:

a. R and RStudio:

b.  Python:

c. MS Azure

A Data Science Microsoft Project Template You Can Use in Your Solutions

3. Better documentation

Save the data + code that generated the output, rather than the output itself. Intermediate files are okay as long as there is clear documentation of how they were created

4. Use Version Control

e.g. using some websites such as Gitlab, GitHub / BitBucket

4. Document and keep track of your analysis environment: If you work on a complex project involving many tools / datasets, the software and computing environment can be critical for reproducing your analysis Computer architecture: CPU (Intel, AMD, ARM), GPUs, Operating system: Windows, Mac OS, Linux / Unix Software toolchain: Compilers, interpreters, command shell, programming languages (C, Perl, Python, etc.), database backends, data analysis software Supporting software / infrastructure: Libraries, R packages, dependencies External dependencies: Web sites, data repositories, remote databases, software repositories

Written Assignments
Get 20% Discount on This Paper
Pages (550 words)
Approximate price: -

Why Choose Us?

Quality Papers

We value our clients. For this reason, we ensure that each paper is written carefully as per the instructions provided by the client. Our editing team also checks all the papers to ensure that they have been completed as per the expectations.

Professional Academic Writers

Over the years, our Written Assignments has managed to secure the most qualified, reliable and experienced team of writers. The company has also ensured continued training and development of the team members to ensure that it keeps up with the rising Academic Trends.

Affordable Prices

Our prices are fairly priced in such a way that ensures affordability. Additionally, you can get a free price quotation by clicking on the "Place Order" button.

On-Time delivery

We pay strict attention to deadlines. For this reason, we ensure that all papers are submitted earlier, even before the deadline indicated by the customer. For this reason, the client can go through the work and review everything.

100% Originality

At Written Assignments, all papers are plagiarism-free as they are written from scratch. We have taken strict measures to ensure that there is no similarity on all papers and that citations are included as per the standards set.

Customer Support 24/7

Our support team is readily available to provide any guidance/help on our platform at any time of the day/night. Feel free to contact us via the Chat window or support email:

Try it now!

Order Now to Get 20% Discount

We'll send you the first draft for approval by at
Total price:

How our best essay writing service works?

Follow these simple steps to get your paper done

Place your order

Fill in the order form and provide all details of your assignment.

Proceed with the payment

Choose the payment system that suits you most.

Receive the final file

Once your paper is ready, we will email it to you.

Our Services

Written Assignments has stood as the world’s leading custom essay writing paper services provider. Once you enter all the details in the order form under the place order button, the rest is up to us.


Cheapest Essay Writing Service

At Written Assignments, we prioritize all aspects that bring about a good grade such as impeccable grammar, proper structure, zero plagiarism and conformance to guidelines. Our experienced team of writers will help you completed your essays and other assignments.


Admission and Business Papers

Be assured that you’ll get accepted to the Master’s level program at any university once you enter all the details in the order form. We won’t leave you here; we will also help you secure a good position in your aspired workplace by creating an outstanding resume or portfolio once you place an order.


Editing and Proofreading

Our skilled editing and writing team will help you restructure your paper, paraphrase, correct grammar and replace plagiarized sections on your paper just on time. The service is geared toward eliminating any mistakes and rather enhancing better quality.


Technical papers

We have writers in almost all fields including the most technical fields. You don’t have to worry about the complexity of your paper. Simply enter as many details as possible in the place order section.