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

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: “Mount the downloaded WebStorm-10*.dmg disk image file as another disk in your system.”

A block of code is set as follows:

iris:
LOAD
RowNo() as id,
    	sepal_length,
    	sepal_width,
    	petal_length,
    	petal_width
FROM [lib://<PATH TO DATAFILE>/iris_test.csv]
(txt, utf8, embedded labels, delimiter is ',', msq);

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

[predictions]:
LOAD * EXTENSION endpoints.ScriptEval('{"RequestType":"endpoint", "endpoint":{"connectionname":"ML demos:Iris"}}', iris);

Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “ If we would like to change our experiment, we can select Configure v2”.

Tips or important notes

Appear like this.