Python Machine Learning Blueprints
上QQ阅读APP看书,第一时间看更新

Preparation

When you are confident you have your data in order, next you will need to prepare it by placing it in a format that is amenable to modeling. This stage encompasses a number of processes, such as filtering, aggregating, imputing, and transforming. The type of actions you need to take will be highly dependent on the type of data you're working with, as well as the libraries and algorithms you will be utilizing. For example, if you are working with natural language-based texts, the transformations required will be very different from those required for time-series data. We'll see a number of examples of these types of transformations throughout the book.