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

Machine Learning Algorithms and Models with Qlik

Machine learning algorithms have become an integral part of our lives, from the personalization of online ads to the recommendation systems on streaming platforms. These algorithms are responsible for making intelligent decisions based on data, without being explicitly programmed.

Machine learning algorithms refer to a set of mathematical models and techniques that enable software to learn patterns and relationships from data, allowing them to make predictions and decisions. These algorithms can be broadly categorized into supervised, unsupervised, semi-supervised, and reinforcement learning algorithms. Each type of algorithm has its own unique characteristics and applications, suiting them to a wide range of tasks.

In this chapter, we will provide an overview of machine learning algorithms and their applications, focusing on algorithms used in Qlik tools. Here is what you will learn as a part of this chapter:

  • Understand...