In this chapter, we started to move a bit closer to implementing a machine learning solution with Qlik tools. We discovered the importance of forming a correct business question to be solved and what aspects should be considered when forming a problem.
We discovered some general steps of data preparation and how these should be handled. More detailed techniques for data modeling and transformations are introduced in Chapter 6. We also investigated the concept of model preparation and validation briefly.
At the end of this chapter, we discussed the importance of presentation and what to consider when visualizing results with Qlik. This topic is considered in more detail in Chapter 9.
In the next chapter, we are going to find out how to prepare environments for our machine learning solutions. We will install on-premises integration for R and Python, discover how to utilize APIs and Advanced Analytics integration to interact with Azure ML Studio and AWS SageMaker, and...