Technical Writing for data science
$10-30 USD
货到付款
Answer the following questions and submit as a PDF. Use an equation editor where necessary. Cite sources where appropriate.
This project is to be completed individually. Do not collaborate with others on this project. Any collaboration or sharing will be considered a violation of the academic integrity policy.
(20 points) Describe a real-world problem that could be solved with a KNN classifier. Identify where you will get the data and how you will train the model. How do you choose the value of number of neighbors k that you will use? Why is the KNN classifier a good choice for this problem?
(20 points) Describe a real-world problem for which the MapReduce programming model would be a good solution. Identify where you will get the data. What is the Mapper for this problem? the Reducer? What makes MapReduce appropriate for this problem?
(20 points) Describe a real-world problem that could be solved by regression. Identify where you will get the data and how you will train the model. How do you choose the regression model? Why is regression the appropriate choice for this problem? What does regression allow you to do for this problem?
(20 points) Why is business important for data scientists? How does data science add value to a business? What business models are relevant for the data age?
(20 points) Describe your plan for your studies in the Data Science program. Present a course plan for your data science degree, identifying how that plan fits the requirements of the program. How does this course plan relate to your career goals in data science?
项目ID： #15900624
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