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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
Toc

Table of Contents (17) Chapters close

Preface 1. Section 1: Machine Learning Basics
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

Importing data from another Excel workbook

Why would we import data from an Excel workbook if we can just open it? The main reason is to take advantage of the transformations we can do using Get & Transform. We will show this by using a file containing real data from the Titanic passengers, which is often used to test machine learning classification models and predict whether a given passenger survived the tragedy or not.

Let's follow some simple steps to load and transform the data. While in a new workbook, follow these steps:

  1. Click on Data.
  2. Navigate to Get Data | From File | From Workbook, as shown in the following screenshot:

The preview window is slightly different to the one we see when opening a CSV file, as you can see in the following screenshot:

In the left part of the preview, you can see a folder named titanic.xls, which represents the file, and below that...

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