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Hands-On Machine Learning with Microsoft Excel 2019

You're reading from   Hands-On Machine Learning with Microsoft Excel 2019 Build complete data analysis flows, from data collection to visualization

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789345377
Length 254 pages
Edition 1st Edition
Tools
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Author (1):
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Julio Cesar Rodriguez Martino Julio Cesar Rodriguez Martino
Author Profile Icon Julio Cesar Rodriguez Martino
Julio Cesar Rodriguez Martino
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Machine Learning Basics FREE CHAPTER
2. Implementing Machine Learning Algorithms 3. Hands-On Examples of Machine Learning Models 4. Section 2: Data Collection and Preparation
5. Importing Data into Excel from Different Data Sources 6. Data Cleansing and Preliminary Data Analysis 7. Correlations and the Importance of Variables 8. Section 3: Analytics and Machine Learning Models
9. Data Mining Models in Excel Hands-On Examples 10. Implementing Time Series 11. Section 4: Data Visualization and Advanced Machine Learning
12. Visualizing Data in Diagrams, Histograms, and Maps 13. Artificial Neural Networks 14. Azure and Excel - Machine Learning in the Cloud 15. The Future of Machine Learning 16. Assessment

Questions

  1. What types of data can be represented in charts? Make a list and think about the best charts to use in each case.
  2. What happens when you try to use a pie chart to show more than five or six data series?
  3. What type of chart would be a good alternative to stacked bars?
  4. Try using other geographical data (for example, street addresses) to create a diagram.
  5. Can you use the US President election data to predict the results for 2020? In principle, it should be possible to forecast the values of the time series. Try it and think about the accuracy of the predictions and the possible explanations.
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