The Illustrated Word2vec – Jay Alammar – Visualizing machine learning one concept at a time
“There is in all things a pattern that is part of our universe. It has symmetry, elegance, and grace - those qualities you find always in that which the true artist captures. You can find it in the turning of the seasons, in the way sand trails along a ridge, in the branch clusters of the creosote bush or the pattern of its leaves. We try to copy these patterns in our lives and our society, seeking the rhythms, the dances, the forms that comfort. Yet, it is possible to see peril in the finding of ultimate perfection. It is clear that the ultimate pattern contains it own fixity. In such perfection, all things move toward death.” ~ Dune (1965) I find the concept of embeddings to be one of the most fascinating ideas in machine learning. If you’ve ever used Siri, Google Assistant, Alexa, Google Translate, or even smartphone keyboard with next-word prediction, then chances are you’ve benefitted from this idea that has become central to Natural Language Processing models.