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Machine Learning with Qlik Sense

Machine Learning with Qlik Sense

By : Hannu Ranta
4.5 (6)
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Machine Learning with Qlik Sense

Machine Learning with Qlik Sense

4.5 (6)
By: Hannu Ranta

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)
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1
Part 1:Concepts of Machine Learning
6
Part 2: Machine learning algorithms and models with Qlik
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12
Part 3: Case studies and best practices

Part 2: Machine learning algorithms and models with Qlik

This section will cover the actual creation of machine learning project using Qlik tools with hands-on examples. The section starts with the setup process required to utilize the tools effectively. Techniques required to preprocess the data with Qlik Sense are covered in Chapter 6 followed by best practices for monitoring the models and handling the deployments. Towards the end of the section, we will cover the functionality of Qlik AutoML using concrete examples. At the end of this section, we will look at the important aspect of visualizing the results.

This section has the following chapters:

  • Chapter 5: Setting Up the Environments
  • Chapter 6: Preprocessing and Exploring Data with Qlik Sense
  • Chapter 7: Deploying and Monitoring Machine Learning Models
  • Chapter 8: Utilising Qlik AutoML
  • Chapter 9: Advanced Data Visualization Techniques for Machine Learning Solutions
...

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