Cover
Title Page
Copyright
Dedication
Contributors
Table of Contents
Preface
Part 1: Concepts of Machine Learning
Chapter 1: Introduction to Machine Learning with Qlik
Introduction to Qlik tools
Insight Advisor
Qlik AutoML
Advanced Analytics Integration
Basic statistical concepts with Qlik solutions
Types of data
Mean, median, and mode
Variance
Standard deviation
Standardization
Correlation
Probability
Defining a proper sample size and population
Defining a sample size
Training and test data in machine learning
Concepts to analyze model performance and reliability
Regression model scoring
Multiclass classification scoring and binary classification scoring
Feature importance
Summary
Chapter 2: Machine Learning Algorithms and Models with Qlik
Regression models
Linear regression
Logistic regression
Lasso regression
Clustering algorithms, decision trees, and random forests
K-means clustering
ID3 decision tree
Boosting algorithms and Naive Bayes
XGBoost
Gaussian Naive Bayes
Neural networks, deep learning, and natural-language models
Summary
Chapter 3: Data Literacy in a Machine Learning Context
What is data literacy?
Critical thinking
Research and domain knowledge
Communication
Technical skills
Informed decision-making
Data strategy
Summary
Chapter 4: Creating a Good Machine Learning Solution with the Qlik Platform
Defining a machine learning problem
Cleaning and preparing data
Example 1
one-hot encoding
Example 2
feature scaling
Preparing and validating a model
Visualizing the end results
Summary
Part 2: Machine learning algorithms and models with Qlik
Chapter 5: Setting Up the Environments
Advanced Analytics Integration with R and Python
Installing Advanced Analytics Integration with R
Installing Advanced Analytics Integration with Python
Setting up Qlik AutoML
Cloud integrations with REST
General Advanced Analytics connector
Amazon SageMaker connector
Azure ML connector
Qlik AutoML connector
Summary
Chapter 6: Preprocessing and Exploring Data with Qlik Sense
Creating a data model with the data manager
Introduction to the data manager
Introduction to Qlik script
Important functions in Qlik script
Validating data
Data lineage and data catalogs
Data lineage
Data catalogs
Exploring data and finding insights
Summary
Chapter 7: Deploying and Monitoring Machine Learning Models
Building a model in an on-premises environment using the Advanced Analytics connection
Monitoring and debugging models
Summary
Chapter 8: Utilizing Qlik AutoML
Features of Qlik AutoML
Using Qlik AutoML in a cloud environment
Creating and monitoring a machine learning model with Qlik AutoML
Connecting Qlik AutoML to an on-premises environment
Best practices with Qlik AutoML