Now, even if you’ve stored a vast amount of well-structured data, it might not be labeled in a way that actually works for training your model. For example, autonomous vehicles don’t just need pictures of the road, they need labeled images where each car, pedestrian, street sign and more are annotated; sentiment analysis projects require labels that help an algorithm understand when someone’s using slang or sarcasm; chatbots need entity extraction and careful syntactic analysis, not just raw language.
In other words, the data you want to use for training usually needs to be enriched or labeled. Or you might just need to collect more of it to power your algorithms. But chances are, the data you’ve stored isn’t quite ready to be used to train your classifiers.https://www.figure-eight.com/resources/what-is-training-data/