Summary
In this chapter, we discovered the usage of Qlik AutoML. We first learned what the tool will provide for users and what its key features are. We built our first machine learning model with Qlik AutoML using the famous Iris dataset. In this section, we discovered how to run experiments and deploy a model from experimentation. We also discovered how to utilize the model in a Qlik application, both during a data load and in real time. We learned from different metrics how our model performed.
In the latter part of this chapter, we took a quick look at an on-premises environment. We learned how to utilize Qlik AutoML in hybrid scenarios and how to set up our environment in these use cases. We also discovered some of the best practices to be used with Qlik AutoML.
In the following chapter, we will dive deep into data visualization. We will discover the techniques to visualize machine-learning-related data and investigate the use of some of the lesser-used graph types. We will...
