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‎pgml-cms/docs/README.md‎

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description:An introduction to key the concepts that power PostgresML.
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description:The key concepts that make up PostgresML.
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#Overview

‎pgml-cms/docs/SUMMARY.md‎

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#Table of contents
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##Introduction
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*[Overview](README.md)
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*[Getting Started](getting-started/README.md)
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*[Create your database](getting-started/create-your-database.md)
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*[Connect your app](getting-started/connect-your-app.md)
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*[Import your data](getting-started/import-your-data.md)
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*[Machine Learning](machine-learning/README.md)
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*[Natural Language Processing](machine-learning/natural-language-processing/README.md)
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*[Embeddings](machine-learning/natural-language-processing/embeddings.md)
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*[Fill Mask](machine-learning/natural-language-processing/fill-mask.md)
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*[Question Answering](machine-learning/natural-language-processing/question-answering.md)
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*[Summarization](machine-learning/natural-language-processing/summarization.md)
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*[Text Classification](machine-learning/natural-language-processing/text-classification.md)
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*[Text Generation](machine-learning/natural-language-processing/text-generation.md)
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*[Text-to-Text Generation](machine-learning/natural-language-processing/text-to-text-generation.md)
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*[Token Classification](machine-learning/natural-language-processing/token-classification.md)
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*[Translation](machine-learning/natural-language-processing/translation.md)
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*[Zero-shot Classification](machine-learning/natural-language-processing/zero-shot-classification.md)
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*[Supervised Learning](machine-learning/supervised-learning/README.md)
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*[Data Pre-processing](machine-learning/supervised-learning/data-pre-processing.md)
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*[Regression](machine-learning/supervised-learning/regression.md)
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*[Classification](machine-learning/supervised-learning/classification.md)
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*[Hyperparameter Search](machine-learning/supervised-learning/hyperparameter-search.md)
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*[Joint Optimization](machine-learning/supervised-learning/joint-optimization.md)
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*[Unsupervised Learning](machine-learning/unsupervised-learning.md)
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*[Vector Database](vector-database.md)
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*[SDKs](sdks/README.md)
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*[Overview](sdks/overview.md)
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*[Getting Started](sdks/getting-started.md)
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*[OpenSourceAI](sdks/opensourceai.md)
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*[Collections](sdks/collections.md)
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*[Pipelines](sdks/pipelines.md)
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*[Search](sdks/search.md)
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*[Tutorials](sdks/tutorials/README.md)
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*[Semantic Search](sdks/tutorials/semantic-search.md)
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*[Semantic Search using Instructor model](sdks/tutorials/semantic-search-using-instructor-model.md)
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*[Extractive Question Answering](sdks/tutorials/extractive-question-answering.md)
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*[Summarizing Question Answering](sdks/tutorials/summarizing-question-answering.md)
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*[Apps](apps/README.md)
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*[Chatbots](apps/chatbots.md)
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*[Fraud Detection](apps/fraud-detection.md)
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*[Recommendation Engine](apps/recommendation-engine.md)
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*[Search](apps/search.md)
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*[Time-series Forecasting](apps/time-series-forecasting.md)
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*[Use cases](use-cases/README.md)
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*[Improve Search Results with Machine Learning](use-cases/improve-search-results-with-machine-learning.md)
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*[Generating LLM embeddings with open source models in PostgresML](use-cases/generating-llm-embeddings-with-open-source-models-in-postgresml.md)
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*[Tuning vector recall while generating query embeddings in the database](use-cases/tuning-vector-recall-while-generating-query-embeddings-in-the-database.md)
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*[Personalize embedding results with application data in your database](use-cases/personalize-embedding-results-with-application-data-in-your-database.md)
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*[LLM based pipelines with PostgresML and dbt (data build tool)](use-cases/llm-based-pipelines-with-postgresml-and-dbt-data-build-tool.md)
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*[Data Storage & Retrieval](data-storage-and-retrieval/README.md)
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*[Tabular data](data-storage-and-retrieval/tabular-data.md)
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*[Vectors](data-storage-and-retrieval/vectors.md)
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*[Documents](data-storage-and-retrieval/documents.md)
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*[Partitioning](data-storage-and-retrieval/partitioning.md)
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*[Deploying PostgresML](deploying-postgresml/README.md)
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*[PostgresML Cloud](deploying-postgresml/postgresml-cloud/README.md)
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*[Plans](deploying-postgresml/postgresml-cloud/plans/README.md)
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*[Serverless databases](deploying-postgresml/postgresml-cloud/plans/serverless-databases.md)
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*[Dedicated databases](deploying-postgresml/postgresml-cloud/plans/dedicated-databases.md)
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*[Self-hosting](deploying-postgresml/self-hosting/README.md)
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*[Pooler](deploying-postgresml/self-hosting/pooler.md)
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*[Building from source](deploying-postgresml/self-hosting/building-from-source.md)
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*[Replication](deploying-postgresml/self-hosting/replication.md)
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*[Backups](deploying-postgresml/self-hosting/backups.md)
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*[Running on EC2](deploying-postgresml/self-hosting/running-on-ec2.md)
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*[PgCat](pgcat/README.md)
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*[Features](pgcat/features.md)
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*[Installation](pgcat/installation.md)
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*[Configuration](pgcat/configuration.md)
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*[Benchmarks](benchmarks/README.md)
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*[PostgresML is 8-40x faster than Python HTTP microservices](benchmarks/postgresml-is-8-40x-faster-than-python-http-microservices.md)
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*[Million Requests per Second](benchmarks/million-requests-per-second.md)
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*[MindsDB vs PostgresML](benchmarks/mindsdb-vs-postgresml.md)
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*[GGML Quantized LLM support for Huggingface Transformers](benchmarks/ggml-quantized-llm-support-for-huggingface-transformers.md)
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*[Making Postgres 30 Percent Faster in Production](benchmarks/making-postgres-30-percent-faster-in-production.md)
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*[Monitoring](monitoring.md)
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*[FAQs](faqs.md)
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*[Developer Docs](developer-docs/README.md)
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*[Local Docker Development](developer-docs/quick-start-with-docker.md)
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*[Installation](developer-docs/installation.md)
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*[Contributing](developer-docs/contributing.md)
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*[Distributed Training](developer-docs/distributed-training.md)
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*[GPU Support](developer-docs/gpu-support.md)
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*[Getting Started](introduction/getting-started/README.md)
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*[Create your database](introduction/getting-started/create-your-database.md)
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*[Connect your app](introduction/getting-started/connect-your-app.md)
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*[Import your data](introduction/getting-started/import-your-data/README.md)
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*[CSV](introduction/getting-started/import-your-data/csv.md)
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*[Foreign Data Wrapper](introduction/getting-started/import-your-data/foreign-data-wrapper.md)
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*[Machine Learning](introduction/machine-learning/README.md)
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*[Natural Language Processing](introduction/machine-learning/natural-language-processing/README.md)
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*[Embeddings](introduction/machine-learning/natural-language-processing/embeddings.md)
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*[Fill Mask](introduction/machine-learning/natural-language-processing/fill-mask.md)
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*[Question Answering](introduction/machine-learning/natural-language-processing/question-answering.md)
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*[Summarization](introduction/machine-learning/natural-language-processing/summarization.md)
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*[Text Classification](introduction/machine-learning/natural-language-processing/text-classification.md)
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*[Text Generation](introduction/machine-learning/natural-language-processing/text-generation.md)
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*[Text-to-Text Generation](introduction/machine-learning/natural-language-processing/text-to-text-generation.md)
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*[Token Classification](introduction/machine-learning/natural-language-processing/token-classification.md)
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*[Translation](introduction/machine-learning/natural-language-processing/translation.md)
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*[Zero-shot Classification](introduction/machine-learning/natural-language-processing/zero-shot-classification.md)
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*[Supervised Learning](introduction/machine-learning/supervised-learning/README.md)
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*[Data Pre-processing](introduction/machine-learning/supervised-learning/data-pre-processing.md)
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*[Regression](introduction/machine-learning/supervised-learning/regression.md)
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*[Classification](introduction/machine-learning/supervised-learning/classification.md)
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*[Hyperparameter Search](introduction/machine-learning/supervised-learning/hyperparameter-search.md)
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*[Joint Optimization](introduction/machine-learning/supervised-learning/joint-optimization.md)
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*[Unsupervised Learning](introduction/machine-learning/unsupervised-learning.md)
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*[SDKs](introduction/machine-learning/sdks/README.md)
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*[Overview](introduction/machine-learning/sdks/overview.md)
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*[Getting Started](introduction/machine-learning/sdks/getting-started.md)
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*[OpenSourceAI](introduction/machine-learning/sdks/opensourceai.md)
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*[Collections](introduction/machine-learning/sdks/collections.md)
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*[Pipelines](introduction/machine-learning/sdks/pipelines.md)
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*[Search](introduction/machine-learning/sdks/search.md)
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*[Tutorials](introduction/machine-learning/sdks/tutorials/README.md)
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*[Semantic Search](introduction/machine-learning/sdks/tutorials/semantic-search.md)
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*[Semantic Search using Instructor model](introduction/machine-learning/sdks/tutorials/semantic-search-using-instructor-model.md)
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*[Extractive Question Answering](introduction/machine-learning/sdks/tutorials/extractive-question-answering.md)
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*[Summarizing Question Answering](introduction/machine-learning/sdks/tutorials/summarizing-question-answering.md)
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##Product
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*[Cloud Database](product/cloud-database/README.md)
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*[Serverless databases](product/cloud-database/serverless-databases.md)
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*[Dedicated](product/cloud-database/dedicated.md)
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*[Enterprise](product/cloud-database/plans.md)
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*[Vector Database](product/vector-database.md)
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*[PgCat Proxy](product/pgcat/README.md)
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*[Features](product/pgcat/features.md)
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*[Installation](product/pgcat/installation.md)
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*[Configuration](product/pgcat/configuration.md)
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##Use Cases
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*[Chatbots](use-cases/chatbots.md)
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*[Search](use-cases/improve-search-results-with-machine-learning.md)
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*[Embeddings](use-cases/embeddings/README.md)
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*[Generating LLM embeddings with open source models in PostgresML](use-cases/embeddings/generating-llm-embeddings-with-open-source-models-in-postgresml/README.md)
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*[Tuning vector recall while generating query embeddings in the database](use-cases/embeddings/generating-llm-embeddings-with-open-source-models-in-postgresml/tuning-vector-recall-while-generating-query-embeddings-in-the-database.md)
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*[Personalize embedding results with application data in your database](use-cases/embeddings/personalize-embedding-results-with-application-data-in-your-database.md)
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*[Time-series Forecasting](use-cases/time-series-forecasting.md)
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*[Fraud Detection](use-cases/fraud-detection.md)
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*[Recommendation Engine](use-cases/recommendation-engine.md)
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##Resources
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*[FAQs](resources/faqs.md)
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*[Data Storage & Retrieval](resources/data-storage-and-retrieval/README.md)
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*[Tabular data](resources/data-storage-and-retrieval/tabular-data.md)
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*[Documents](resources/data-storage-and-retrieval/documents.md)
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*[Partitioning](resources/data-storage-and-retrieval/partitioning.md)
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*[LLM based pipelines with PostgresML and dbt (data build tool)](resources/data-storage-and-retrieval/llm-based-pipelines-with-postgresml-and-dbt-data-build-tool.md)
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*[Benchmarks](resources/benchmarks/README.md)
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*[PostgresML is 8-40x faster than Python HTTP microservices](resources/benchmarks/postgresml-is-8-40x-faster-than-python-http-microservices.md)
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*[Million Requests per Second](resources/benchmarks/million-requests-per-second.md)
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*[MindsDB vs PostgresML](resources/benchmarks/mindsdb-vs-postgresml.md)
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*[GGML Quantized LLM support for Huggingface Transformers](resources/benchmarks/ggml-quantized-llm-support-for-huggingface-transformers.md)
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*[Making Postgres 30 Percent Faster in Production](resources/benchmarks/making-postgres-30-percent-faster-in-production.md)
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*[Developer Docs](resources/developer-docs/README.md)
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*[Local Docker Development](resources/developer-docs/quick-start-with-docker.md)
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*[Installation](resources/developer-docs/installation.md)
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*[Contributing](resources/developer-docs/contributing.md)
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*[Distributed Training](resources/developer-docs/distributed-training.md)
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*[GPU Support](resources/developer-docs/gpu-support.md)
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*[Deploying PostgresML](resources/developer-docs/deploying-postgresml/README.md)
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*[Monitoring](resources/developer-docs/deploying-postgresml/monitoring.md)
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*[Self-hosting](resources/developer-docs/self-hosting/README.md)
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*[Pooler](resources/developer-docs/self-hosting/pooler.md)
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*[Building from source](resources/developer-docs/self-hosting/building-from-source.md)
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*[Replication](resources/developer-docs/self-hosting/replication.md)
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*[Backups](resources/developer-docs/self-hosting/backups.md)
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*[Running on EC2](resources/developer-docs/self-hosting/running-on-ec2.md)

‎pgml-cms/docs/apps/README.md‎

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* A PgCat pooling proxy to provide secure access and model load balancing across tens of thousands of clients
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* A web application to manage deployed models and host SQL notebooks
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By building PostgresML on top of a mature database, we get reliable backups for model inputs and proven scalability without reinventing the wheel, so that we can focus on providing access to the latest developments in open source machine learning and artificial intelligence.
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#Createyour database
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##Sign up for an account
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Visit[https://postgresml.org/signup](https://postgresml.org/signup)​ to create a new account with your email, Google or Github authentication.
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Click on**Get Started** under the plan of your choice.
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<figure><imgsrc="../../.gitbook/assets/image (7).png"alt=""><figcaption></figcaption></figure>
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###Your database credentials <ahref="#create-a-new-account"id="create-a-new-account"></a>
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We'll automatically provision an initial set of database credentials and provide you with the connection string. You can connect to your database if you have`psql` installed on your machine, or any other PostgreSQL client.
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#Import your data
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Machine learning always depends on input data, whether it's generating text with pretrained LLMs, training a retention model on customer data, or predicting session abandonment in real time. Just like any PostgreSQL database, PostgresML can be configured as the authoritative application data store, a streaming replica from some other primary, or use foreign data wrappers to query another data host on demand. Depending on how frequently your data changes and where your authoritative data resides, different methodologies imply different tradeoffs.
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PostgresML can easily ingest data from your existing data stores.&#x20;
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###Static data
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Data that changes infrequently can be easily imported into PostgresML using`COPY`. All you have to do is export your data as a CSV file, create a table in Postgres to store it, and import it using the command line.
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{% content-ref url="csv.md" %}
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[csv.md](csv.md)
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{% endcontent-ref %}
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###Live data
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Importing data from online databases can be done with foreign data wrappers. Hosted PostgresML databases come with both`postgres_fdw` and`dblink` extensions pre-installed, so you can import data from any of your existing Postgres databases, and export machine learning artifacts from PostgresML using just a few lines of SQL.
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{% content-ref url="foreign-data-wrapper.md" %}
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[foreign-data-wrapper.md](foreign-data-wrapper.md)
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{% endcontent-ref %}
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####
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#CSV
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Data that changes infrequently can be easily imported into PostgresML using`COPY`. All you have to do is export your data as a CSV file, create a table in Postgres to store it, and import it using the command line.
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Let's use a simple CSV file with 3 columns as an example:
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| name| text| John|
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| age| integer| 30|
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| is\_paying\_user| boolean| true|
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####Export data as CSV
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If you're using a Postgres database already, you can export any table as CSV with just one command:
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If you're using another data store, it should almost always provide a CSV export functionality, since CSV is the most commonly used data format in machine learning.
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####Create table in Postgres
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name TEXT,
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age INTEGER,
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);
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```
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####Import data using the command line
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Once you have a table and your data exported as CSV, importing it can also be done with just one command:
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We took our export command and changed`TO` to`FROM`, and that's it. Make sure you're connecting to your PostgresML database when importing data.
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####Refreshing data
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If your data changed, repeat this process again. To avoid duplicate entries in your table, you can truncate (or delete) all rows beforehand:
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```
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TRUNCATE your_table;
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```

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