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pgml-docs/README.md

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---
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description: Page to navigate to any part of documentation
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---
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# Home
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* [getting-started](getting-started/ "mention")
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* [natural-language-processing](machine-learning/natural-language-processing/ "mention")
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* [vector-database.md](vector-database.md "mention")
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* [supervised-learning](machine-learning/supervised-learning/ "mention")
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* [unsupervised-learning.md](machine-learning/unsupervised-learning.md "mention")
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* [sdks](sdks/ "mention")
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* [chatbots.md](apps/chatbots.md "mention")
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* [use-cases](use-cases/ "mention")
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* [benchmarks](benchmarks/ "mention")
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* [monitoring.md](monitoring.md "mention")
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* [developer-docs](developer-docs/ "mention")

pgml-docs/SUMMARY.md

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# Table of contents
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* [Home](README.md)
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* [Overview](overview.md)
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* [Getting Started](getting-started/README.md)
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* [Sign up](getting-started/sign-up.md)
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* [Select a plan](getting-started/select-a-plan.md)
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* [Database Credentials](getting-started/database-credentials.md)
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* [Connect to the Database](getting-started/connect-to-the-database.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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* [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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* [PgCat](pgcat.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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* [Quick Start with Docker](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)

pgml-docs/apps/README.md

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# Apps
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Easy to use no-code interfaces to build and deploy end-to-end ML powered applications. These will serve as solutions that can be used as is or reference architectures for applications that need customization. For instance: `pgml-chat` is a no-code command line app, that allows anyone to build an interactive chatbot for slack or discard on top of their private knowledge base.

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