[SOLVED] Data Science For Business

Data Science for BusinessFinal projectDescription: The goal of this final project is to have students work as a team and demonstrate the ability to follow the main steps of a Machine Learning project and develop a Machine Learning model. Each group has to select a dataset either from the links that are provided, or you can find yours from any other resource. The final project includes the basic steps that require students to master data science skills to solve a multiclass classification problem. Students are expected to work as groups and each group member has to actively participate in the final project activities.Project Policy: It is likely that some members will not be active or not participate in the final project. However, this is NOT a legitimate reason for you not being able to turn in your final project on time. If you do care about your grade and project, you have to find a solution for this situation. In fact, the group project also can be done independently. I list the policies as follows:1. Each group consists of two students only.2. Students may opt out of a group and conduct the final project independently.3. Whatever option you choose, you must inform the instructor4. There is NO free ride for the final project. Each group member has to make equal contributions to the final project.5. Failure to participate in group discussions/meetings may result in a zero point of your final projects toward your final grade.6. Failure to present your final project successfully may lead to a lower grade for your final project.Getting the DatasetThe first task is to find a labeled dataset that can be used for multiclass classification problem (only two classes). In this project, the best choice is to have a real-world data, not just artificial datasets. In order for you to have the greatest chance of success with the final project, it is important that you choose a manageable dataset.1. The dataset should be readily accessible and large enough. As such, your dataset must have at least 100 records and between 2 to 6 measurements (exceptions can be made but you must discuss with me first).2. The dataset should be qualified for solving multiclass classification problem.3. The dataset must have two labeled classes only.4. To assist you in choosing a feasible problem and dataset, each team should check with the instructor by email about your project idea for approval by 04/18/2021.5. Informal discussions with the professor can help to refine the project.6. No two teams can work on the same dataset .7. Here are some links you can check to get data (but not limited to, so you can still do your search and find a dataset) :Popular open data repositories:UC Irvine Machine Learning Repository: http://archive.ics.uci.edu/ml/index.phpKaggle datasets: https://www.kaggle.com/datasetsAmazon’s AWS datasets: https://registry.opendata.aws/Data Portals: http://dataportals.org/Open Data Monitor: https://opendatamonitor.eu/frontend/web/index.php?r=dashboard%2FindexProject RequirementsRun the K-Nearest Neighbors model in Python to predict the class label from the different measurements in the dataset.1. Introduction: Start with an introduction of your project. This introduction should introduce (1) the problem you want to solve. (2) Dataset descriptions like the size, the number of measurements, the type of the measurements, and the number of classes and their labels.2. Load the data and discover & visualize it to get insights: generate graphs to discover if there is any relationship between measurements or find any clustering.3. Prepare the dataset: Do preprocessing if your dataset needs for example, dimension reduction, removing outliers, handling text and categorical variables, cleaning the data, and/or data standardization (all of the variables used for K-NN model must be on the same order of magnitude in order to produce accurate results.4. Data partitioning: After preprocessing your dataset, you need now to split the dataset into non-overlap sets to perform training and testing phases.5. Different values of K : Choose three different values of K. Discuss your reasons for choosing the different values of K.6. Training Phase : Run the model using the three different values of K you chose in the previous step. Discuss the three main steps in the K-NN algorithm: calculate the distance, find the nearest neighbors, and making predictions.7. Testing Phase :Compare the accuracy between the training phase and the testing phase. Discuss this results8. Evaluation Phase : Check the accuracy of all models predictions (the different values of K) by creating the confusion matrix, compute Recall score, and Precision score. Discuss the predictions results in terms of the accuracy and the misclassification error.9. Present the best model : choose the best model you found based on the results from the evaluation phase. Think of any improvement that can be made to get better results.10. Conclusion : Discuss your final results and conclusion about the model.Project ReportA narrative description of the all the machine learning model steps, provided with screen shots of the code and output.For every step in the project requirements list above do: (1) Discuss what you did. (2) Provide screen shots of the code. Provide screen shots of the output. (3) Provide any graphs if needs.Presentation Deliverables (PowerPoints slides)You should record your screen while you are doing the presentation and submit the recording. Every member of the group should participate in the recording. There are different options you can use. One of them is using Kaltura Recording. Your recording may be added to a folder on Canvas so all other students in the class can view it.Submission Checklist:1. Dataset file: original file and the modified one in case if you did any modifications.2. Python file (.py)3. Report document.4. PowerPoint slides.5. Recorded Presentation.All the above documents should be submitted on 05/02/2021 11:59 PM. Include all files in one folder and compress your folder (.zip)

Don't use plagiarized sources. Get Your Custom Essay on
[SOLVED] Data Science For Business
Get a 15% discount on this Paper
Order Essay
Quality Guaranteed

With us, you are either satisfied 100% or you get your money back-No monkey business

Check Prices
Make an order in advance and get the best price
Pages (550 words)
$0.00
*Price with a welcome 15% discount applied.
Pro tip: If you want to save more money and pay the lowest price, you need to set a more extended deadline.
We know that being a student these days is hard. Because of this, our prices are some of the lowest on the market.

Instead, we offer perks, discounts, and free services to enhance your experience.
Sign up, place your order, and leave the rest to our professional paper writers in less than 2 minutes.
step 1
Upload assignment instructions
Fill out the order form and provide paper details. You can even attach screenshots or add additional instructions later. If something is not clear or missing, the writer will contact you for clarification.
s
Get personalized services with My Paper Support
One writer for all your papers
You can select one writer for all your papers. This option enhances the consistency in the quality of your assignments. Select your preferred writer from the list of writers who have handledf your previous assignments
Same paper from different writers
Are you ordering the same assignment for a friend? You can get the same paper from different writers. The goal is to produce 100% unique and original papers
Copy of sources used
Our homework writers will provide you with copies of sources used on your request. Just add the option when plaing your order
What our partners say about us
We appreciate every review and are always looking for ways to grow. See what other students think about our do my paper service.
Psychology
Thanks so very much. The paper is well-researched and adequately referenced. You have been of great help during the pandemic!
Customer 452467, January 31st, 2021
Human Resources Management (HRM)
Thanks for the paper.
Customer 452701, September 15th, 2023
Management
Comprehensively done. Thank you
Customer 452583, July 20th, 2021
Philosophy
excellent job i will be coming back for any future papers if I have too.
Customer 452611, October 11th, 2021
Human Resources Management (HRM)
Thank you so much.
Customer 452701, August 15th, 2023
Social Work and Human Services
Great Work!
Customer 452587, October 13th, 2021
IT, Web
Paper was great and accomplished everything I needed.
Customer 452885, October 27th, 2022
Social Work and Human Services
Excellent!
Customer 452587, August 3rd, 2021
Human Resources Management (HRM)
You did an awesome job with this paper. Thanks for the prompt delivery.
Customer 452701, October 24th, 2023
Other
AWESOME
Customer 452813, June 19th, 2022
Other
great
Customer 452813, June 30th, 2022
Nursing
Did not receive paper on time.
Customer 452693, November 9th, 2022
Enjoy affordable prices and lifetime discounts
Use a coupon FIRST15 and enjoy expert help with any task at the most affordable price.
Order Now Order in Chat

We now help with PROCTORED EXAM. Chat with a support agent for more details