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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

Data Literacy in a Machine Learning Context

As we enter the age of artificial intelligence and machine learning, it’s becoming increasingly important to develop a foundational understanding of data literacy. In this chapter, we will explore the concept of data literacy and its critical role in the world of machine learning.

Data literacy refers to the ability to read, analyze, and understand data. With the rapid growth of data in our daily lives, data literacy has become a crucial skill for individuals, businesses, and organizations alike. In the context of machine learning, data literacy is especially important, as it forms the backbone of the entire process.

Machine learning models are only as good as the data they’re trained on, and data literacy plays a vital role in ensuring that the data used for training is of high quality, relevant, and free of bias.

In this chapter, we’re going to cover the following main topics:

  • Data literacy and the...
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