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

Creating a Good Machine Learning Solution with the Qlik Platform

This chapter provides an overview of the key steps involved in creating effective machine learning solutions with Qlik. The same principles apply to all machine learning tools and solutions.

The process starts with defining the problem to be solved and aligning it with the organization’s goals. Data preparation is critical and Qlik provides robust data preparation capabilities for collecting, cleaning, and transforming data to ensure its quality and relevance.

Data exploration and visualization using Qlik’s features are essential for understanding data patterns and informing the machine learning model. Model selection is crucial and Qlik offers a wide range of algorithms for different use cases.

Once the model is selected, it needs to be trained using the corresponding tools. Model evaluation using appropriate metrics helps assess its performance and make necessary refinements.

Deployment of...