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Machine Learning with Qlik Sense: Utilize different machine learning models in practical use cases by leveraging Qlik Sense
by 作者: Hannu Ranta (Author)
Publisher Finelybook 出版社: Packt Publishing (October 27, 2023)
Language 语言: English
pages 页数: 242 pages
ISBN-10 书号: 1805126156
ISBN-13 书号: 9781805126157
Book Description
Master the art of machine learning by using the one-of-a-kind Qlik platform, and take your data analytics skills to the next level
Key Features
Gain a solid understanding of machine learning concepts and learn to effectively define a problem
Explore the application of machine learning principles within the Qlik platform
Apply your knowledge of ML to real-world scenarios with the help of practical examples
Purchase of the print or Kindle book includes a free PDF eBook
Book Description
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.
What you will learn
Find out how to build practical machine learning solutions with the Qlik platform
Develop the skills needed to generate and verify machine learning models using the Qlik platform
Discover techniques used for preparing and investigating data to craft machine learning solutions
Understand how to transform real-world business problems into machine learning models
Expand your potential to new use cases with data analytics
Explore advanced visualization techniques to make your models come alive
Who this book is for
If you’re interested in data and analytics and are looking to extend your skillset to machine learning, this book is for you. Basic working knowledge of data, preferably with Qlik tools, will help you get started with this book. This is an excellent guide for anyone who wants to start using machine learning as part of their data analytics journey.
Table of Contents
1. Introduction to [vlachine Learning with Qlik
2. vlachine Learning Algorithms and [vlodels with Qlik
3. Data Literacy in Ivlachine Learning Context
4. Creating a Good Mlachine Learning Solution with the Qlik Platform
5. Setting Up the Environments
6. Preprocessing and Exploring Data with Qlik Sense
7. Deploying and [vlonitoring Ivlachine Learning Ivlocdels
8. Utilizing Qlik AutolvlL
9. Acvanced Data Visualisation Techniques for Machine Learning Soluti ons
o.Exampes and Case studies
11. Future Direction
About the Author
Hannu Ranta is a top-notch data and cloud professional with a wide technical knowledge. He has worked with big data, IoT and analytics solutions with the largest enterprises across the globe. While having a problem-solving mindset, he always enjoys finding new innovative solutions to help customers to deliver value. Hannu obtained his Master of Science degree with distinction in 2015 and has worked in leading data companies like Qlik, Microsoft and Cubiq Analytics since then. Currently he is a Principal Enterprise Architect for Nordic region at Qlik. Amazon page
