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Improving Product Search with Learning to Rank - part three
This is the third blog post on applying learning to rank to enhance E-commerce search.
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Ilya Pavlov
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Vespa Newsletter, November 2022
Vespa features and performance advances include ANN Pre-Filter Performance, Parent Field Hit-Estimates, Model Training Notebooks, and GCP Support.
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Carl Campbell
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Improving Product Search with Learning to Rank - part two
This is the second blog post on applying learning to rank to enhance E-commerce search.
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NASA
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Vespa Cloud on Google Cloud Platform
Vespa Cloud is now available on Google Cloud Platform
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Pawel Czerwinski
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Improving Product Search with Learning to Rank - part one
This is the first blog post on applying learning to rank to enhance E-commerce search.
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Scott Graham
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Vespa Newsletter, October 2022
Advances in Vespa features and performance include a BertBase Embedder / model hub, improved query performance, paged attributes, ARM64 support and term bolding in string arrays.
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julien Tromeur
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Building Billion-Scale Vector Search - part two
Searching billion-scale datasets without breaking the bank.
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Niek Doup
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Vespa on ARM64
Vespa is now released as a multiplatform container image, supporting both x86_64 and ARM64.
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Arnaud Mariat
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Building Billion-Scale Vector Search - part one
How fast is fast? Many consider the blink of an eye, around 100-250ms, to be plenty fast.
Pre-trained models on Vespa Cloud
Vespa Cloud now provides pre-trained ML models for your applications
Text embedding made simple
Vespa now lets you create a production quality semantic search application from scratch in minutes
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Ilya Pavlov
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Vespa Newsletter, September 2022
Advances in Vespa features and performance include rank-phase statistics, detailed rank performance analysis, new query- and trace-applications and a new training video!
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