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


Visualizing machine learning data is a crucial step in the data analysis process, enabling you to gain insights, identify patterns, and communicate results effectively. In this chapter, we familiarized ourselves with the different visualizations and techniques to visualize machine learning data. At the beginning of this chapter, we discovered common principles for creating a good visualization and familiarized ourselves with the key principles of coloring.

Toward the end of the chapter, we discovered some different visualization types that Qlik offers natively and learned how to use some of the graph types effectively. We learned the principles of the most used visualizations and how to fine-tune these in Qlik while keeping the context of machine learning in mind.

In the next chapter, we will look at the actual use cases of the machine learning solutions. We will learn how to build a few different machine learning models and applications from scratch and utilize all we...