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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 took a closer look at model creation and deployment using Advanced Analytics Integration and the server-side R extension in an on-premises environment (having done the initial environment setup in Chapter 5).

We started our journey in this chapter by getting familiar with the two concepts of utilizing Advanced Analytics Integration. We then took a closer look at an on-the-fly data analytics use case and created a k-means clustering example with real-time integration with R.

We built a simple dashboard to support our analysis and took a deeper look at the Advanced Analytics Integration syntax. In the latter part of this chapter, we learned how to debug and monitor our models running in on-premises environments.

In the next chapter, we will shift our focus toward Qlik AutoML. We will learn the implementation model used with AutoML and how to utilize this tool both in Qlik Cloud and on-premises. We will also learn how to deploy and monitor models using...

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