* [speeding-up-vector-recall-5x-with-hnsw.md](speeding-up-vector-recall-5x-with-hnsw.md "mention")

* [how-to-improve-search-results-with-machine-learning.md](how-to-improve-search-results-with-machine-learning.md "mention")

* [pgml-chat-a-command-line-tool-for-deploying-low-latency-knowledge-based-chatbots-part-i.md](pgml-chat-a-command-line-tool-for-deploying-low-latency-knowledge-based-chatbots-part-i.md "mention")

* [postgresml-is-8-40x-faster-than-python-http-microservices.md](postgresml-is-8-40x-faster-than-python-http-microservices.md "mention")

* [postgres-full-text-search-is-awesome.md](postgres-full-text-search-is-awesome.md "mention")

* [oxidizing-machine-learning.md](oxidizing-machine-learning.md "mention")

* [data-is-living-and-relational.md](data-is-living-and-relational.md "mention")

* [Home](README.md)

* [Speeding up vector recall 5x with HNSW](speeding-up-vector-recall-5x-with-hnsw.md)

* [How-to Improve Search Results with Machine Learning](how-to-improve-search-results-with-machine-learning.md)

* [pgml-chat: A command-line tool for deploying low-latency knowledge-based chatbots](pgml-chat-a-command-line-tool-for-deploying-low-latency-knowledge-based-chatbots-part-i.md)

* [Announcing GPTQ & GGML Quantized LLM support for Huggingface Transformers](announcing-gptq-and-ggml-quantized-llm-support-for-huggingface-transformers.md)

* [Making Postgres 30 Percent Faster in Production](making-postgres-30-percent-faster-in-production.md)

* [MindsDB vs PostgresML](mindsdb-vs-postgresml.md)

* [PostgresML raises $4.7M to launch serverless AI application databases based on Postgres](postgresml-raises-usd4.7m-to-launch-serverless-ai-application-databases-based-on-postgres.md)

* [PG Stat Sysinfo, a Postgres Extension for Querying System Statistics](pg-stat-sysinfo-a-postgres-extension-for-querying-system-statistics.md)

* [PostgresML as a memory backend to Auto-GPT](postgresml-as-a-memory-backend-to-auto-gpt.md)

PostgresML makes it easy to use machine learning with your database and to scale workloads horizontally in our cloud. One of the most common use cases is to improve search results. In this article, we'll show you how to build a search engine from the ground up, that leverages multiple types of natural language processing (NLP) and machine learning (ML) models to improve search results, including vector search and personalization with embeddings.