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Extract usable features from high-dimensional data

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

State of the art results with significantly less data and training time

We have embeddings specialized for specific domains. This lets you get the benefits of transfer learning, without the expensive data gathering and pretraining steps.

See our specialized embeddings

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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