Python: Real World Machine Learning

Creating a feature set

The most important factor involved in successful machine learning is the quality of your input data. A good model with misleading, inappropriately normalized, or uninformative data will not see the same level of success anywhere near a model run over appropriately prepared data.

In some cases, you have the ability to specify data collection or have access to a useful, sizeable, and varied set of source data. With the right knowledge and skillset, you can use this data to create highly useful feature sets.

In general, having a strong knowledge as to how to construct good feature sets is very helpful as it enables you to audit and assess any new dataset for missed opportunities. In this chapter, we will introduce a design process ...