Machine Learning with Qlik Sense

Machine Learning with Qlik Sense

by Hannu Ranta
Released October 2023
Publisher(s): Packt Publishing
ISBN: 9781805126157

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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. Machine Learning with Qlik Sense
  2. Contributors
  3. About the author
  4. About the reviewers
  5. Preface
    1. Who this book is for
    2. What this book covers
    3. To get the most out of this book
    4. Download the example code files
    5. Conventions used
    6. Get in touch
    7. Share Your Thoughts
    8. Download a free PDF copy of this book
  6. Part 1:Concepts of Machine Learning
  7. Chapter 1: Introduction to Machine Learning with Qlik
    1. Introduction to Qlik tools
      1. Insight Advisor
      2. Qlik AutoML
      3. Advanced Analytics Integration
    2. Basic statistical concepts with Qlik solutions
      1. Types of data
      2. Mean, median, and mode
      3. Variance
      4. Standard deviation
      5. Standardization
      6. Correlation
      7. Probability
    3. Defining a proper sample size and population
      1. Defining a sample size
      2. Training and test data in machine learning
    4. Concepts to analyze model performance and reliability
      1. Regression model scoring
      2. Multiclass classification scoring and binary classification scoring
      3. Feature importance
    5. Summary
  8. Chapter 2: Machine Learning Algorithms and Models with Qlik
    1. Regression models
      1. Linear regression
      2. Logistic regression
      3. Lasso regression
    2. Clustering algorithms, decision trees, and random forests
      1. K-means clustering
      2. ID3 decision tree
    3. Boosting algorithms and Naive Bayes
      1. XGBoost
      2. Gaussian Naive Bayes
    4. Neural networks, deep learning, and natural-language models
    5. Summary
  9. Chapter 3: Data Literacy in a Machine Learning Context
    1. What is data literacy?
      1. Critical thinking
      2. Research and domain knowledge
      3. Communication
      4. Technical skills
    2. Informed decision-making
    3. Data strategy
    4. Summary
  10. Chapter 4: Creating a Good Machine Learning Solution with the Qlik Platform
    1. Defining a machine learning problem
    2. Cleaning and preparing data
      1. Example 1 – one-hot encoding
      2. Example 2 – feature scaling
    3. Preparing and validating a model
    4. Visualizing the end results
    5. Summary
  11. Part 2: Machine learning algorithms and models with Qlik
  12. Chapter 5: Setting Up the Environments
    1. Advanced Analytics Integration with R and Python
      1. Installing Advanced Analytics Integration with R
      2. Installing Advanced Analytics Integration with Python
    2. Setting up Qlik AutoML
    3. Cloud integrations with REST
      1. General Advanced Analytics connector
      2. Amazon SageMaker connector
      3. Azure ML connector
      4. Qlik AutoML connector
    4. Summary
  13. Chapter 6: Preprocessing and Exploring Data with Qlik Sense
    1. Creating a data model with the data manager
      1. Introduction to the data manager
    2. Introduction to Qlik script
      1. Important functions in Qlik script
    3. Validating data
    4. Data lineage and data catalogs
      1. Data lineage
      2. Data catalogs
    5. Exploring data and finding insights
    6. Summary
  14. Chapter 7: Deploying and Monitoring Machine Learning Models
    1. Building a model in an on-premises environment using the Advanced Analytics connection
    2. Monitoring and debugging models
    3. Summary
  15. Chapter 8: Utilizing Qlik AutoML
    1. Features of Qlik AutoML
    2. Using Qlik AutoML in a cloud environment
    3. Creating and monitoring a machine learning model with Qlik AutoML
    4. Connecting Qlik AutoML to an on-premises environment
    5. Best practices with Qlik AutoML
    6. Summary
  16. Chapter 9: Advanced Data Visualization Techniques for Machine Learning Solutions
    1. Visualizing machine learning data
    2. Chart and visualization types in Qlik
      1. Bar charts
      2. Box plots
      3. Bullet charts
      4. Distribution plots
      5. Histogram
      6. Maps
      7. Scatter plots
      8. Waterfall charts
      9. Choosing visualization type
    3. Summary
  17. Part 3: Case studies and best practices
  18. Chapter 10: Examples and Case Studies
    1. Linear regression example
    2. Customer churn example
    3. Summary
  19. Chapter 11: Future Direction
    1. The future trends of machine learning and AI
    2. How to recognize potential megatrends
    3. Summary
  20. Index
    1. Why subscribe?
  21. Other Books You May Enjoy
    1. Packt is searching for authors like you
    2. Share Your Thoughts
    3. Download a free PDF copy of this book

Product information

  • Title: Machine Learning with Qlik Sense
  • Author(s): Hannu Ranta
  • Release date: October 2023
  • Publisher(s): Packt Publishing
  • ISBN: 9781805126157