Building scalable semantic retrieval from image, text, graph, and interaction data
We live in a world with an explosion of information. There are millions of clothes, songs, movies, recipes, cars, houses, which one should you pick? Semantic search can find the right one for any taste and wish!
In this article, I will introduce what is semantic search, what can be built with it, and how to build it. For example, why do people look for clothes? They like the brand, the color, the shape, or the price. All these aspects can be used to find the best one.
Embeddings are amazing! Do you want to learn how to build a visual search engine using any image dataset? I built a python library to demo it, and I will explain here how you can build your own embeddings
There are a lot of things that are intuitive and obvious to us about the world. For example, two instances of the same category look like the same thing, we can recognize which flower looks like another, without even knowing its name. And we can do the same thing with many kinds of objects.
This skill allows…
Recently I’ve been reading and experimenting a lot with computer vision, here is an introduction of what is interesting to learn and use in that domain.
Computer vision has advanced a lot in recent years. Those are the topics I will mention here :
Machine learning engineer interested in representation learning, computer vision, natural language processing and programming (distributed systems, algorithms)