node2vec: Embeddings for Graph Data – Towards Data Science

Embeddings… A word that every data scientist has heard by now, but mostly in the context of NLP. So why do we even bother embedding stuff? As I see it, creating quality embeddings and feeding it into models, is the exact opposite of the famous say "Garbage in, garbage out" . When you feed low quality data into your models, you put the entire load of learning on your model, as it will have to learn all the necessary conclusions that could be derived from the data. On the contrary, when you use quality embeddings, you already put some knowledge in your data and thus make the task of learning the problem easier for your models.