Extract usable features from high-dimensional data

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Word2vec for anything

Basilica is an API that embeds high-dimensional data like images and text. You send us e.g. an image, and we send you back a vector of floats. You can feed these features into traditional ML algorithms like linear regression or k-means clustering.

Learn how to train an image model with Basilica

Simple API, many ways to use it

  • Product Recommendation
  • Asset Pricing
  • Fighting Trolls
  • Job Candidate Clustering

How does it work?

Basilica uses a technique called “embedding” to transform high-dimensional data into usable features. It’s similar to other embeddings you may be familiar with, like word2vec.

We produce these embeddings by training deep neural networks to perform a mix of tasks on private and public data. The intermediate layers of these networks learn to recognize general features in the data, which we send back to you as a vector of floats.

Using these embeddings lets you integrate high-dimensional data into existing models with very little effort. Embeddings are also a form of transfer learning -- because we train the embeddings on millions of data points, you can get very good results even if your high-dimensional dataset is very small.

Read more in our FAQ

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