In this module will you will learn how early discoveries in your data can help refine hypotheses, data, and performance of initial Qlik AutoML models. It will also explore feature engineering, which is the process of creating new features from current ones. Finally, it will cover how to review the features in your dataset to determine what possible issues may exist and how to fix them, including finding and solving for data leakage.
Learning Objectives:
- Assist you in inspecting potential data sources
- Determining whether your data is viable
- Help create a descriptive analysis for ML
- Inform dataset design from summarized insights