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Machine Learning with Qlik Sense

You're reading from   Machine Learning with Qlik Sense Utilize different machine learning models in practical use cases by leveraging Qlik Sense

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781805126157
Length 242 pages
Edition 1st Edition
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Author (1):
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Hannu Ranta Hannu Ranta
Author Profile Icon Hannu Ranta
Hannu Ranta
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Table of Contents (17) Chapters Close

Preface 1. Part 1:Concepts of Machine Learning
2. Chapter 1: Introduction to Machine Learning with Qlik FREE CHAPTER 3. Chapter 2: Machine Learning Algorithms and Models with Qlik 4. Chapter 3: Data Literacy in a Machine Learning Context 5. Chapter 4: Creating a Good Machine Learning Solution with the Qlik Platform 6. Part 2: Machine learning algorithms and models with Qlik
7. Chapter 5: Setting Up the Environments 8. Chapter 6: Preprocessing and Exploring Data with Qlik Sense 9. Chapter 7: Deploying and Monitoring Machine Learning Models 10. Chapter 8: Utilizing Qlik AutoML 11. Chapter 9: Advanced Data Visualization Techniques for Machine Learning Solutions 12. Part 3: Case studies and best practices
13. Chapter 10: Examples and Case Studies 14. Chapter 11: Future Direction 15. Index 16. Other Books You May Enjoy

Linear regression example

In this example, we will create a linear regression model to predict the value of a house in the California area. Let’s begin by getting familiar with the dataset. We will use a common California house values dataset. This is a collection of data related to residential real estate properties in various regions of California, USA. It is commonly used in machine learning and data analysis tasks for predicting house prices based on various features.

The dataset we will use contains the following fields:

  • medianIncome: The median income of households in a specific block.
  • housingMedianAge: The median age of houses in a block.
  • totalRooms: The total number of rooms in the houses in a block.
  • totalBedrooms: The total number of bedrooms in the houses in a block.
  • population: The total population of the block.
  • households: The total number of households (a group of people residing within a home unit) within a block.
  • latitude: The...
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