Book Image

Machine Learning with Qlik Sense

By : Hannu Ranta
Book Image

Machine Learning with Qlik Sense

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

Visualizing the end results

When visualizing the end results, we have several options to consider in separate parts of the machine learning solution creation. We will take a deeper look into visualization techniques and different chart types in Chapter 9. However, here are some general steps to consider:

  • Load data: Load your machine learning results data into Qlik Sense either using data sources or direct connection to Qlik AutoML or third-party machine learning platforms. This data can include predicted values, actual values, model evaluation metrics, and other relevant information.
  • Create visualizations: Use Qlik Sense’s built-in visualization tools to create visual representations of your machine learning results. You can choose from various chart types depending on the type of data and the insights you want to convey. Planning a clean and visually appealing user interface is an important step.
  • Customize visualizations: Customize the appearance and properties...