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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

Summary

In this chapter, we started to move a bit closer to implementing a machine learning solution with Qlik tools. We discovered the importance of forming a correct business question to be solved and what aspects should be considered when forming a problem.

We discovered some general steps of data preparation and how these should be handled. More detailed techniques for data modeling and transformations are introduced in Chapter 6. We also investigated the concept of model preparation and validation briefly.

At the end of this chapter, we discussed the importance of presentation and what to consider when visualizing results with Qlik. This topic is considered in more detail in Chapter 9.

In the next chapter, we are going to find out how to prepare environments for our machine learning solutions. We will install on-premises integration for R and Python, discover how to utilize APIs and Advanced Analytics integration to interact with Azure ML Studio and AWS SageMaker, and...

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