Data Science Toolkit Integration

Beginning with Fusion 5.0, data scientists and machine learning engineers can deploy end-user-trained Python machine learning models to Fusion using the Data Science Toolkit Integration (DSTI). This offers real-time prediction and seamless integration with query and index pipelines.

Benefits:

  • Extension points for data scientists to plug in customized Python modeling code

  • Client libraries to ease the development and testing of Python plugins

  • API-driven and dynamic, runtime loading and updating of plugins

Example use cases:

  • Using SpaCy to extract named entities and indexing results into a Solr collection

  • Using a Keras model to perform query intent classification at query time

  • Using pre-trained word embeddings to generate synonyms for a query

See these topics for complete details: