What this book covers
Chapter 1, Getting Ready with Predictive Analytics, explains the key concepts of predictive analytics and how to install our learning environments, such as Qlik Sense, R, and Rattle.
Chapter 2, Preparing Your Data, covers the basic characteristics of datasets, how to load a dataset into Rattle, and how to transform it. As data is the basic ingredient of analytics, preparing the data to analyze it is the first step.
Chapter 3, Exploring and Understanding Your Data, introduces you to Exploratory Data Analysis (EDA) using Rattle. EDA is a statistical approach to understanding data.
Chapter 4, Creating Your First Qlik Sense Application, discusses how to load a dataset into Qlik Sense, create a data model and basic charts, and explore data using Qlik Sense. Using Exploratory Data Analysis and Rattle to understand our data is a very mathematical approach. Usually, business users prefer a more intuitive approach, such as Qlik Sense
Chapter 5, Clustering and Other Unsupervised Learning Methods, covers machine, supervised, and unsupervised learning but focuses on unsupervised learning We create an example application using K-means, a classic machine learning algorithm. We use Rattle to process the dataset and then we load it into Qlik Sense to present the data to the business user.
Chapter 6, Decision Trees and Other Supervised Learning Methods, focuses on supervised learning. It helps you create an example application using Decision Tree Learning. We use Rattle to process the data and Qlik Sense to communicate with it.
Chapter 7, Model Evaluation, explains how to evaluate the performance of a model. Model evaluation is very useful to improve the performance.
Chapter 8, Visualizations, Data Applications, Dashboards, and Data Storytelling, focuses on data visualization and data storytelling using Qlik Sense.
Chapter 9, Developing a Complete Application, explains how to create a complete application. It covers how to explore the data, create a predictive model, and create a data application.
