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


In this chapter, we utilized the skills learned during the previous chapters by implementing two different use cases. In our first example, we studied the data of houses in California and created a model to predict their prices based on house-related variables. We created an application to utilize our model and learned about the iterations and how to interpret the experiment results.

In our second example, we learned how to form a customer churn model and utilize it in multiple ways. We also learned how to create different datasets from our original data file and how to form a machine learning question using a framework. We visualized the results using native visualizations in Qlik Sense.

In our next and last chapter, we will look into the future. We will investigate current trends in machine learning and artificial intelligence and try to predict how these might evolve in the future. We will also investigate megatrends and get familiar with the characteristics of a megatrend...