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Sharing Vespa at the SF Big Analytics Meetup

By Jon Bratseth, Distinguished Architect, Oath

Vespa at Zedge - providing personalization content to millions of iOS, Android & web users

This blog post describes Zedge’s use of Vespa for search and recommender systems to support content discovery for personalization of mobile phones (Android, iOS and Web). Zedge is now using...

Introducing JSON queries

We recently introduced a new addition to the Search API - JSON queries. The search request can now be executed with a POST request, which includes the query-parameters within its...

Introducing ONNX support

ONNX (Open Neural Network eXchange) is an open format for the sharing of neural network and other machine learned models between various machine learning and deep learning frameworks. As the...

Parent-child in Vespa

Parent-child relationships let you model hierarchical relations in your data. This blog post talks about why and how we added this feature to Vespa, and how you can use it...

Scaling TensorFlow model evaluation with Vespa

In this blog post we’ll explain how to use Vespa to evaluate TensorFlow models over arbitrarily many data points while keeping total latency constant. We provide benchmark data from our...

Introducing TensorFlow support

In previous blog posts we have talked about Vespa’s tensor API which enables some advanced ranking capabilities. The primary use case is for machine learned ranking, where you train your...

Optimizing realtime evaluation of neural net models on Vespa

In this blog post we describe how we recently made neural network evaluation over 20 times faster on Vespa’s tensor framework.

Blog recommendation with neural network models

Update 2021-05-20: This blog post refers to Vespa sample applications that do not exist anymore. Please refer to the News search and recommendation tutorial for an updated version of text...