Product developers’ guide to model training — Part 1: Qualitative data
TLDR
Machines have a hard time understanding data humans can read. Apply encoding on qualitative data to train models more efficiently.
#Outline
- Introduction
- Before we begin
- Qualitative data
- Encoding data
- Conclusion
Introduction
Most applications will have collected big data in their lifetime of usage. This data is extremely useful to their business to make improvements, but is also applicable to developing AI solutions. Machine learning is an AI solution that is best done when a company has a sufficient amount of data to detect patterns and behaviors, from ranking the present to predicting the future. In this guide, we’ll look at how to clean big data so machines may interpret it faster, more accurately, and remain human interpretable.
