Creating a Good Machine Learning Solution with the Qlik Platform
This chapter provides an overview of the key steps involved in creating effective machine learning solutions with Qlik. The same principles apply to all machine learning tools and solutions.
The process starts with defining the problem to be solved and aligning it with the organization’s goals. Data preparation is critical and Qlik provides robust data preparation capabilities for collecting, cleaning, and transforming data to ensure its quality and relevance.
Data exploration and visualization using Qlik’s features are essential for understanding data patterns and informing the machine learning model. Model selection is crucial and Qlik offers a wide range of algorithms for different use cases.
Once the model is selected, it needs to be trained using the corresponding tools. Model evaluation using appropriate metrics helps assess its performance and make necessary refinements.