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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

What is data literacy?

As stated previously, data literacy refers to the ability to read, analyze, and understand data. It encompasses a range of skills, including the ability to read and interpret data visualizations, understand statistical concepts, and apply critical thinking to data analysis. Data literacy is becoming increasingly important in today’s data-driven world, as individuals and organizations are faced with ever-growing amounts of data that need to be analyzed and interpreted in order to make informed decisions.

In many fields, such as business, healthcare, and government, data literacy has become a crucial skill, and it’s also vital in the field of machine learning, where models are only as good as the data they are trained on.

Data literacy is not just about technical skills, but also includes the ability to critically evaluate data and identify potential biases or limitations. It involves a mindset of curiosity, skepticism, and a willingness to...

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