Metric learning, a supervised branch of representation learning, is a useful dimensionality reduction approach to learn a meaningful representation of your data. It's used both for visualization purposes of high-dimensional datasets, and in several applications in computer vision, NLP & recommendation engines. Join us, and add this useful and underutilized tool to your data scientist's toolkit.
In this tutorial will cover several topics:
We'll combine all that goodness in a notebook, together with an NLP example to classify customer service queries, and using state-of-the-art sentence transformers & an interactive visualization library, we'll showcase how DML can utilize supervision improve on the general-purpose sentence embedding.