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Machine Learning with Qlik Sense
By :

Machine Learning with Qlik Sense
By:
Overview of this book
The ability to forecast future trends through data prediction, coupled with the integration of ML and AI, has become indispensable to global enterprises. Qlik, with its extensive machine learning capabilities, stands out as a leading analytics platform enabling businesses to achieve exhaustive comprehension of their data. This book helps you maximize these capabilities by using hands-on illustrations to improve your ability to make data-driven decisions.
You’ll begin by cultivating an understanding of machine learning concepts and algorithms, and build a foundation that paves the way for subsequent chapters. The book then helps you navigate through the process of framing machine learning challenges and validating model performance. Through the lens of Qlik Sense, you'll explore data preprocessing and analysis techniques, as well as find out how to translate these techniques into pragmatic machine learning solutions. The concluding chapters will help you get to grips with advanced data visualization methods to facilitate a clearer presentation of findings, complemented by an array of real-world instances to bolster your skillset.
By the end of this book, you’ll have mastered the art of machine learning using Qlik tools and be able to take your data analytics journey to new heights.
Table of Contents (17 chapters)
Preface
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Part 1:Concepts of Machine Learning
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Chapter 1: Introduction to Machine Learning with Qlik
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Chapter 2: Machine Learning Algorithms and Models with Qlik
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Chapter 3: Data Literacy in a Machine Learning Context
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Chapter 4: Creating a Good Machine Learning Solution with the Qlik Platform
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Part 2: Machine learning algorithms and models with Qlik
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Chapter 5: Setting Up the Environments
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Chapter 6: Preprocessing and Exploring Data with Qlik Sense
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Chapter 7: Deploying and Monitoring Machine Learning Models
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Chapter 8: Utilizing Qlik AutoML
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Chapter 9: Advanced Data Visualization Techniques for Machine Learning Solutions
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Part 3: Case studies and best practices
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Chapter 10: Examples and Case Studies
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Chapter 11: Future Direction
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Index
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