Feature Engineering Made Easy

Summary

Feature engineering is a massive task to be undertaken by data scientists and machine learning engineers. It is a task that is imperative to having successful and production-ready machine learning pipelines. In the coming seven chapters, we are going to explore six major aspects of feature engineering:

• Feature understanding: learning how to identify data based on its qualities and quantitative state
• Feature improvement: cleaning and imputing missing data values in order to maximize the dataset's value
• Feature selection -statistically selecting and subsetting feature sets in order to reduce the noise in our data
• Feature construction - building new features with the intention of exploiting feature interactions
• Feature transformation ...