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Hands-On Machine Learning with Microsoft Excel 2019

You're reading from  Hands-On Machine Learning with Microsoft Excel 2019

Product type Book
Published in Apr 2019
Publisher Packt
ISBN-13 9781789345377
Pages 254 pages
Edition 1st Edition
Languages
Author (1):
Julio Cesar Rodriguez Martino Julio Cesar Rodriguez Martino
Profile icon Julio Cesar Rodriguez Martino

Table of Contents (17) Chapters

Preface Section 1: Machine Learning Basics
Implementing Machine Learning Algorithms Hands-On Examples of Machine Learning Models Section 2: Data Collection and Preparation
Importing Data into Excel from Different Data Sources Data Cleansing and Preliminary Data Analysis Correlations and the Importance of Variables Section 3: Analytics and Machine Learning Models
Data Mining Models in Excel Hands-On Examples Implementing Time Series Section 4: Data Visualization and Advanced Machine Learning
Visualizing Data in Diagrams, Histograms, and Maps Artificial Neural Networks Azure and Excel - Machine Learning in the Cloud The Future of Machine Learning Assessment

Chapter 6, Data Mining Models in Excel Hands-On Examples

  1. Use the previous knowledge of the business to discard these associations.
  2. Not necessarily. These types of analysis are usually dependent on the business domain and even on the particular place where we perform them. This means that some results can be generalized, but, often, not all of them.
  3. It means that there is no customer that started buying products by the time indicated in the column and that kept buying after the period of time shown in the row.
  4. There are no customers that old (in terms of time spent as customers).
  5. For example, focusing on those that stop buying and aiming ad campaigns at them.
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