Data Science

Data Science for Business project Due Date 04/28/2021Description: The goal of this project is to have students demonstrate the ability to follow the main steps of a Machine Learning project and develop a Machine Learning model. Each student 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.The dataset: the excelProject Requirements: Run 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.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.

Discuss The Application Of Data To Problem-Solving For more information on Data read this: https://en.wikipedia.org/wiki/Data

Case Study: Proposing a Data Gathering Approach at TLG Solutions (pages 171 – 175)Read the TLG Solutions case and consider the following questions:1. What is the client requesting, and what goal does the client have for this project?2. What are the presenting problems?? What do you believe may be any underlying problems?? Which of these underlying problems is most likely? Why?3. What data would illustrate whether these underlying problems are occurring?? Which method of data gathering would you use and why? (Consider using the method of analysis shown in Table 7.2.)4. Write a proposal that explains what data you will gather through what means (interviews, surveys, focus groups, observations, and/or unobtrusive measures). Include any questions you might ask, observations you would undertake, and/or documents you would want to gather.5. What are the advantages and disadvantages of your data gathering choice(s)?6. Include a rationale and proposed timeline for your approach and any details about the data gathering method itself, including possible interview or survey questions, documents to gather, or observations you would conduct.7. Finally, ensure that your proposal addresses any additional contracting needs you may have in your relationship with Greenfield.MIN 8 PEER review REFERENCES For more information on Data Gathering  read this: https://en.wikipedia.org/wiki/Data_collection

During the past 6 weeks, you have been introduced to multiple knowledge areas, including health data quality, access, retention, data sets, and electronic health records. In addition to assessing some of the knowledge about EHRs and EHR standards, this week we will review some important concepts, which you will also see in the final exam. You may start the review by selecting one of the questions below. Please try to read the answers prior to yours and try to address a different question in order to make the midterm exam review more complete and meaningful. Some more new questions will be added throughout the week. What is the purpose and value of the EHR standards? Illustrate by briefly describing one of them, such as HL7, ASTM E1384-07, LOINC, or RxNorm. What is the importance of clinical decision support systems and what integration or interfaces need to be in place for it to work effectively? What are some policies, processes, or rules that need to change as an organization transitions from the paper or hybrid environment to a fully electronic health record? What are the data sets? Select one of the existing health data sets and discuss its value in improving population health or healthcare delivery in the US. Explain electronic document management systems along with brief explanations of their components. For more information on Health Data Quality read this: https://en.wikipedia.org/wiki/Data_quality

Discussion: Biometric System Evaluation Learning Objectives and Outcomes Identify the correct advantages of each biometric methodIdentify the correct disadvantages of each biometric method Assignment RequirementsRead the worksheet named “Biometric System Evaluation” and address the following:Using what you have learned about the biometric method, identify the correct advantages and disadvantages of each listed biometric type.Respond to your peers with your point of view on their answers. Respond to at least two of your classmates’ original thread posts with between 100 – 150 words for each reply.  Make sure your opinion is substantiated with valid reasons and references to the concepts covered in the course. In addition, initiate a discussion with the students who comment on your answer.Required ResourcesWorksheet: Biometric System Evaluation (ws_biometricsystemeval)

Do some research and statistics on Facebook. Like their target audience, strengths/weaknesses for company usage, the main ways company’s use the platform to connect with users, etc. 

Requirements 1) APA 6th Ed format 2 ) Due 28 Nov  3) 3-4 Pages (not including title page and references) 4) 3 References 5) Plagiarism-Free Assignment Discuss a database system used in a company or an organization (It could be your organization or any other organization). Your paper should cover the following topics: Why it is necessary to use a database system? What kinds of information this database system collect? and what information it provides? Which database management system is used? Access? Oracle? DB2 …? Why or why not it is a good choice? Any other topics you would like to discuss related to this database system? Your paper should be 3-4 pages in length, and reflect your personal experiences with this issue.

 A few weeks ago, many of you completed your research projects on NoSQL, open-source, or OO databases. What are some of the advantages that OO Databases offer that even the most advanced RDBMS cannot offer in the enterprise setting? Please provide three advantages and provide a business use case illustrating these examples. 

Question of original discussion-  After studying this week’s assigned readings, discuss the following:1.  What are the business costs or risks of poor data quality? Support your discussion with at least 3 references.2.  What is data mining? Support your discussion with at least 3 references.3.  What is text mining? Support your discussion with at least 3 references. Please use APA throughout. Read and respond to at least two (2) of your classmates (attached below). In your response to your classmates, consider comparing your articles to those of your classmates. Below are additional suggestions on how to respond to your classmates’ discussions: Ask a probing question, substantiated with additional background information, evidence, or research. Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives. Offer and support an alternative perspective using readings from the classroom or from your own research. Validate an idea with your own experience and additional research. Make a suggestion based on additional evidence drawn from readings or after synthesizing multiple postings. Expand on your colleagues’ postings by providing additional insights or contrasting perspectives based on readings and evidence.150 words for each author. APA format. 

To enhance the security of information systems, enterprises are developing and adopting information system management systems. However, if an information management system is exploited, applications and the data they contain will be compromised. Therefore, it is important to perform a comprehensive security analysis throughout the enterprise. In your own words explain the purpose of a ‘security analysis’,  Please state your answer in a  2 page paper in APA format.  Include citations and sources in APA style. For more information read this: https://en.wikipedia.org/wiki/Security_analysis