Isye 6501 homework 1 - Study guides, Class notes & Summaries

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ISYE 6501 Homework 15 (ESSAY).
  • ISYE 6501 Homework 15 (ESSAY).

  • Essay • 4 pages • 2022
  • ISYE 6501 Homework 15 (ESSAY). Question 20.1 Describe analytics models that could be used to help the company monetize their data: How could the company use these data sets to generate value, and what analytics models might they need to do it? There are lots of good answers, and I want you to think about two types – at least one of your answers should be based on just one data set (the one they’ve collected internally on customer browsing patterns on the website), and at least one of yo...
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ISYE 6501 Homework 12: Power Company Case. All Questions and answers, Graded A+, 2022 update.
  • ISYE 6501 Homework 12: Power Company Case. All Questions and answers, Graded A+, 2022 update.

  • Exam (elaborations) • 4 pages • 2023
  • ISYE 6501 Homework 12: Power Company Case. All Questions and answers, Graded A+, 2022 update. Document Content and Description Below ISYE 6501 Homework 12: Power Company Case In approaching the power company case study, I find it best to break the problem into three more discrete and manageable parts. For each of these parts we c an then better define the specific data needs, model usage, and results for each individual part. Then, it is possible bring these individually addressed issues toget...
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ISyE 6501 Homework 15
  • ISyE 6501 Homework 15

  • Essay • 3 pages • 2021
  • ISyE 6501 Homework 15 Question 20.1 Describe analytics models that could be used to help the company monetize their data: How could the company use these data sets to generate value, and what analytics models might they need to do it? There are lots of good answers, and I want you to think about two types – at least one of your answers should be based on just one data set (the one they’ve collected internally on customer browsing patterns on the website), and at least one of your other...
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ISYE 6501 Week 1 Slides, Check out the preview, 100% Proven pass rate, Document Content and Description Below
  • ISYE 6501 Week 1 Slides, Check out the preview, 100% Proven pass rate, Document Content and Description Below

  • Exam (elaborations) • 35 pages • 2023
  • ISYE 6501 Week 1 Slides, Check out the preview, 100% Proven pass rate, Document Content and Description Below ISYE 6501 Week 1 Slides HomeWork #1 EDX GTx: ISYE6501x - Introduction to Analytics Modeling Mónica Rojas May 17, 2020 Table of Contents Results................................................. ............................................................................................................1 Question 2.1 ..........................................................................
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Georgia tech ISYE 6501 Week 4 homework Exponential Smoothing Document Content and Description Below
  • Georgia tech ISYE 6501 Week 4 homework Exponential Smoothing Document Content and Description Below

  • Exam (elaborations) • 96 pages • 2023
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  • Georgia tech ISYE 6501 Week 4 homework Exponential Smoothing Document Content and Description Below ISYE 6501 Week 4 homework Exponential Smoothing Exponential smoothing assists with change detection as it smoothes out the data. The benfits of exponential smoothing are that it gives you smoother data (less noisy data) and the ability to forecast using trends and seanolaity for time series data. Additionally, data can be made to be less noisy for more confidence in a CUSUM change detection mode...
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ISYE 6501- Homework 1 Michael Chapman August 23, 2018, Georgia Tech, Questions with accurate answers
  • ISYE 6501- Homework 1 Michael Chapman August 23, 2018, Georgia Tech, Questions with accurate answers

  • Exam (elaborations) • 11 pages • 2023
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  • ISYE 6501- Homework 1 Michael Chapman August 23, 2018, Georgia Tech, Questions with accurate answers Document Content and Description Below ISYE 6501- Homework 1 Michael Chapman August 23, 2018 Question 2.1 In my current job, I am responsible for understanding my company’s customer experience feedback when processing an insurance c laim on their mobile device. This feedback is typically in the form of a survey. The main metric we use to gauge customer satisfaction is Net Promoter Score (NPS)...
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Georgia Tech ISYE - 6501 Homework 2 Due Date: Thursday, September 3rd, 2020, Graded A+
  • Georgia Tech ISYE - 6501 Homework 2 Due Date: Thursday, September 3rd, 2020, Graded A+

  • Exam (elaborations) • 9 pages • 2023
  • Available in package deal
  • Georgia Tech ISYE - 6501 Homework 2 Due Date: Thursday, September 3rd, 2020, Graded A+ Document Content and Description Below ISYE - 6501 Homework 2 Due Date: Thursday, September 3rd, 2020 Contents 1 ISYE - 6501 Homework 2 2 2 Homework Analysis 2 2.1 Analysis 3.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 Analysis 4.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.3 Analysis 4.2 . . . . . . ...
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Georgia tech ISYE 6501 OAN - Homework Week 4, Questions and answers, Graded A+, 2022/2023
  • Georgia tech ISYE 6501 OAN - Homework Week 4, Questions and answers, Graded A+, 2022/2023

  • Exam (elaborations) • 19 pages • 2023
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  • Georgia tech ISYE 6501 OAN - Homework Week 4, Questions and answers, Graded A+, 2022/2023 Document Content and Description Below ISYE 6501 OAN - Homework Week 4 Contents 1 Question 7.1 1 2 Question 7.2 2 2.1 Set up . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 Load and examine the data for this assignment . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.3 Convert temps data to vector . . . . . . . . . . . . . . . . . . . . . . . ...
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Intro Analytics Modeling - ISYE-6501 Homework 10, Questions with accurate answers.
  • Intro Analytics Modeling - ISYE-6501 Homework 10, Questions with accurate answers.

  • Exam (elaborations) • 10 pages • 2023
  • Intro Analytics Modeling - ISYE-6501 Homework 10, Questions with accurate answers. Document Content and Description Below Intro Analytics Modeling - ISYE-6501 Homework 10 Question 14.1 The breast cancer data set . 1. Use the mean/mode imputation method to impute values for the missing data. 2. Use regression to impute values for the missing data. 3. Use regression with perturbation to impute values for the missing data 4. (Optional) Compare the results and quality of classification models (e.g...
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