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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

Summary

In this chapter, we learned about two data mining techniques: Market Basket Analysis and Customer Cohort Analysis. The first one tells us about hidden relations between store departments or products based on the customers' behavior. The second shows the time evolution of the number of customers, revealing differences between different customer segments or cohorts.

There are a large number of data mining analyses that can help us dig into our datasets and find hidden information, which is extremely important in order for us to understand our business and make the right decisions.

In the next chapter, we will study a special kind of dataset in detail: time series. We will see that it needs a different kind of modeling and analysis.

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