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Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 29 (from laksa055)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa029.int.ahrefs:8124/' \
  -H 'Content-Type: text/plain' \
  -H 'X-ClickHouse-Database: crawler3' \
  -H 'Authorization: Basic YXBpOg==' \
  -d 'SELECT getAhrefsURLFromUnparsed(src_unparsed) AS found_url, ifNull(toUnixTimestamp(download_stamp), 0) AS crawl_time, ifNull(toUnixTimestamp(props_url_first_seen), 0) AS first_indexed_time, download_http_code AS http_code, src_unparsed AS src_unparsed, src_root_hash AS src_root_hash, history_drop_reason AS history_drop_reason, meta_title AS meta_title, meta_descriptions AS meta_descriptions, attrs_boilerpipe_text AS attrs_boilerpipe_text, attrs_markdown AS attrs_markdown, attrs_readable_markdown AS attrs_readable_markdown, meta_canonical AS meta_canonical FROM crawler3.page_info_local FINAL PREWHERE (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://fastdatascience.com/natural-language-processing/natural-language-processing-expert/\')), getAhrefsUnparsedNoserviceFromURL(\'https://fastdatascience.com/natural-language-processing/natural-language-processing-expert/\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/fastdatascience.com\/natural-language-processing\/natural-language-processing-expert\/","crawl_time":1776338157,"first_indexed_time":1720420587,"http_code":200,"src_unparsed":"com,fastdatascience!\/natural-language-processing\/natural-language-processing-expert\/ s443","src_root_hash":"5796097362812707029","history_drop_reason":null,"meta_title":"Natural Language Processing Expert","meta_descriptions":["Natural Language Processing Expert Explains: If your company has a large number of unstructured documents such as CVs, inspection reports, health records, or otherwise, and you are struggling to extract value from them, you could be sitting on a gold mine of data and it might be time to call in a Natural Language Processing expert. Or maybe your organisation needs to build a chatbot, or analyse and triage emails? In any case our company of NLP experts Fast Data Science can help."],"attrs_boilerpipe_text":"Natural Language Processing Expert Explains:\nIf your company has a large number of unstructured documents such as CVs, inspection reports, health records, or otherwise, and you are struggling to extract value from them, you could be sitting on a gold mine of data and it might be time to call in a\nNatural Language Processing\nexpert. Or maybe your organisation needs to build a chatbot, or analyse and triage emails? In any case our company of NLP experts Fast Data Science can help.\nWhat is Natural Language Processing\n(NLP)? NLP is a discipline within artificial intelligence dealing with analysis of human language. With NLP we can interpret documents written by humans, for humans. NLP also includes natural language dialogue systems such as Siri on the iPhone, as well as speech recognition and speech synthesis systems, and search engines! So you might be using NLP systems every day without realising.\nNatural language processing\nhas its roots in the 1950s. Already in 1950,\nAlan Turing\npublished an article titled “Computing Machinery and Intelligence” which proposed what is now called the Turing test as a criterion of\nintelligence\n\/, a task that involves the automated interpretation and generation of natural language (e.g. “We are searching in the database”), but at the time not articulated as a problem separate from artificial intelligence.\nNatural Language Processing Experts Fast Data Science\nAt Fast Data Science we take pride in our\nnatural language processing\nexpertise (NLP). We offer expertise in many areas of data science and our main area of focus is NLP. The manager, Thomas Wood, studied a Masters in 2008 at Cambridge University in\nComputer Speech, Text and Internet Technology\nand since then he has been working exclusively in machine learning and mostly in NLP. In 2018 he founded Fast Data Science to deliver data science expertise, focusing on NLP. You can read the bios of Thomas Wood and the other Natural Language Processing Experts in our team on the\nteam page\n. In addition to building NLP pipelines from scratch, our team has worked on\nnatural language dialogue systems\n, document classifiers and text based recommender systems. For these tasks, we have used both traditional machine learning techniques as well as the state of the art such as deep learning, convolutional neural networks,\nBERT\n, and the like. You can read a post about transformers (the current cutting-edge NLP model) by Thomas Wood on deepai.org\nhere\n. Our NLP experts normally use\nPython\nbut we can adapt to your organisation’s preferred technology stack.\nFast Data Science - London\nNeed a business solution?\nNLP, ML and data science leader since 2016 - get in touch for an NLP brainstorming session.\nOur NLP Expertise\nAs a company of Natural Language Experts, we work in all areas of NLP, and are happy to discuss your NLP problem with you. Our NLP expertise includes:\nNatural language understanding\nText analysis\nTopic analysis – clustering, unsupervised learning\nDocument classification\nDocument-based recommender systems\nUnstructured data analysis\nDocument anonymisation - for example replacing names and addresses with fake entities, this is an ever-expanding need of businesses in the post-GDPR and HIPAA world.\nAn NLP Expert can deliver a variety of results for your business\nExperts in NLP and unstructured data\nToday many companies, in particular in certain industries such as healthcare, pharmaceuticals, legal, and insurance, have large amounts of unstructured data. This is typically data in text format, which may even be unscanned documents, PDFs, HTML, or any other file type.\nUnstructured data is very difficult to deal with but can contain a goldmine of information. Fast Data Science specialises in extracting value from organisations’ unstructured datasets.\nNatural Language Processing applications in healthcare\nAI and natural language processing are being increasingly adopted across the healthcare sector.\nThis technology is sometimes called healthtech or MedTech. NLP is being\nused\nto compare and detect changes in clinical reports, extract clinical concepts such as MeSH terms from electronic medical records, and develop human-to-machine natural language dialogue systems to improve the healthcare experience.\nNatural Language Processing technologies at Fast Data Science\nAs NLP experts, we do a lot of natural language processing with Python. We have worked on a variety of NLP models, including:\nBag of words, tf*idf, cosine similarity\nNLP pipelines, lemmatisation, parsers, chunkers\nDeep neural networks\nconvolutional neural networks (text as well as images)\nRNN, LSTM\nSeq2seq, word2vec, doc2vec\nsee a live demo of a CNN for author identification\nClustering: Latent Dirichlet Allocation\nThis is useful for extracting topics from a set of unstructured documents, for example legal documents, survey responses, factory error reports, etc.\nSearch engines and search term recommenders\nGoogle Natural Language, AWS, Microsoft Azure\nTopic detection is an NLP technique that allows you to discover common themes in a set of unstructured documents.\nNatural Language Processing in Python and R\nWe work with the following programming languages and frameworks:\nTensorFlow\nKeras\nPython NLTK\nR\nExamples of past Natural Language Processing projects\nNLP projects we have worked on for major household names include\na spoken dialogue system to control a smart home\nan unsupervised text analysis program to analyse text descriptions of manufacturing defects (\nBoehringer Ingelheim\n)\na model to classify jobseekers’ CVs into industries and salary bands (\nCV-Library\n).\nanalysis of survey responses (\nWhite Ribbon Alliance\n)","attrs_markdown":"[Fast Data Science® ![Fast Data Science®](https:\/\/fastdatascience.com\/images\/logo.svg)](https:\/\/fastdatascience.com\/)\n\nToggle main menu\n\nServices\n\n[Data science services overview](https:\/\/fastdatascience.com\/services\/)\n\n[Machine learning hands-on development](https:\/\/fastdatascience.com\/data-science-consulting\/machine-learning-consulting\/)\n\n[AI strategy consulting](https:\/\/fastdatascience.com\/ai-for-business\/ai-strategy-consulting\/)\n\n[Fractional head of AI](https:\/\/fastdatascience.com\/ai-for-business\/fractional-head-of-ai\/)\n\n[Technical due diligence on AI companies](https:\/\/fastdatascience.com\/ai-due-diligence\/)\n\n[Training courses and workshops](https:\/\/fastdatascience.com\/training-and-upskilling-analytics-teams-in-data-science\/)\n\nTools\n\n[Clinical Trial Risk Tool](https:\/\/fastdatascience.com\/ai-in-pharma\/clinical-trial-risk-tool\/)\n\n[NLP dashboard](https:\/\/fastdatascience.com\/natural-language-processing\/nlp-dashboard\/)\n\n[Harmony (data harmonisation)](https:\/\/fastdatascience.com\/ai-in-research\/harmony-wellcome-data-prize\/)\n\n[Drug Names Plugin](https:\/\/fastdatascience.com\/ai-in-pharma\/drug-name-recogniser\/)\n\n[UK Company Details plugin](https:\/\/fastdatascience.com\/uk-company-details\/)\n\n[Company name recognition](https:\/\/fastdatascience.com\/natural-language-processing\/company-named-entity-recognition\/)\n\n[Author identification](https:\/\/fastdatascience.com\/natural-language-processing\/forensic-stylometry-linguistics-authorship-analysis\/)\n\n[Insolvency Bot (legal Q\\&A)](https:\/\/fastdatascience.com\/insolvency\/)\n\nSkills\n\n[Skills overview](https:\/\/fastdatascience.com\/skills\/)\n\n[Natural language processing](https:\/\/fastdatascience.com\/natural-language-processing\/)\n\n[Cloud machine learning](https:\/\/fastdatascience.com\/ai-for-business\/cloud-machine-learning-consulting\/)\n\n[Predictive analytics](https:\/\/fastdatascience.com\/data-science-consulting\/predictive-analytics-consulting\/)\n\n[Conversion optimisation](https:\/\/fastdatascience.com\/ai-for-business\/conversion-optimisation\/)\n\n[Deep learning](https:\/\/fastdatascience.com\/data-science-consulting\/deep-learning-consulting\/)\n\n[Case studies](https:\/\/fastdatascience.com\/case-studies\/) [Blog](https:\/\/fastdatascience.com\/blog\/)\n\nAbout\n\n[Team](https:\/\/fastdatascience.com\/team\/)\n\n[Resources](https:\/\/fastdatascience.com\/resources\/)\n\n[Company info](https:\/\/fastdatascience.com\/fast-data-science-company\/)\n\n[Contact](https:\/\/fastdatascience.com\/contact\/)\n\nEn\n\n- [De](https:\/\/fastdatascience.com\/de\/verarbeitung-nat%C3%BCrlicher-sprache\/experte-f%C3%BCr-nat%C3%BCrliche-sprachverarbeitung\/)\n\n[Contact](https:\/\/fastdatascience.com\/contact\/)\n\n[Services](https:\/\/fastdatascience.com\/natural-language-processing\/natural-language-processing-expert\/)\n\n[Data science services overview](https:\/\/fastdatascience.com\/services\/) [Machine learning hands-on development](https:\/\/fastdatascience.com\/data-science-consulting\/machine-learning-consulting\/) [AI strategy consulting](https:\/\/fastdatascience.com\/ai-for-business\/ai-strategy-consulting\/) [Fractional head of AI](https:\/\/fastdatascience.com\/ai-for-business\/fractional-head-of-ai\/) [Technical due diligence on AI companies](https:\/\/fastdatascience.com\/ai-due-diligence\/) [Training courses and workshops](https:\/\/fastdatascience.com\/training-and-upskilling-analytics-teams-in-data-science\/)\n\n[Tools](https:\/\/fastdatascience.com\/natural-language-processing\/natural-language-processing-expert\/)\n\n[Clinical Trial Risk Tool](https:\/\/fastdatascience.com\/ai-in-pharma\/clinical-trial-risk-tool\/) [NLP dashboard](https:\/\/fastdatascience.com\/natural-language-processing\/nlp-dashboard\/) [Harmony (data harmonisation)](https:\/\/fastdatascience.com\/ai-in-research\/harmony-wellcome-data-prize\/) [Drug Names Plugin](https:\/\/fastdatascience.com\/ai-in-pharma\/drug-name-recogniser\/) [UK Company Details plugin](https:\/\/fastdatascience.com\/uk-company-details\/) [Company name recognition](https:\/\/fastdatascience.com\/natural-language-processing\/company-named-entity-recognition\/) [Author identification](https:\/\/fastdatascience.com\/natural-language-processing\/forensic-stylometry-linguistics-authorship-analysis\/) [Insolvency Bot (legal Q\\&A)](https:\/\/fastdatascience.com\/insolvency\/)\n\n[Skills](https:\/\/fastdatascience.com\/natural-language-processing\/natural-language-processing-expert\/)\n\n[Skills overview](https:\/\/fastdatascience.com\/skills\/) [Natural language processing](https:\/\/fastdatascience.com\/natural-language-processing\/) [Cloud machine learning](https:\/\/fastdatascience.com\/ai-for-business\/cloud-machine-learning-consulting\/) [Predictive analytics](https:\/\/fastdatascience.com\/data-science-consulting\/predictive-analytics-consulting\/) [Conversion optimisation](https:\/\/fastdatascience.com\/ai-for-business\/conversion-optimisation\/) [Deep learning](https:\/\/fastdatascience.com\/data-science-consulting\/deep-learning-consulting\/)\n\n[Case studies](https:\/\/fastdatascience.com\/case-studies\/) [Blog](https:\/\/fastdatascience.com\/blog\/)\n\n[About](https:\/\/fastdatascience.com\/natural-language-processing\/natural-language-processing-expert\/)\n\n[Team](https:\/\/fastdatascience.com\/team\/)\n\n[Resources](https:\/\/fastdatascience.com\/resources\/)\n\n[Company info](https:\/\/fastdatascience.com\/fast-data-science-company\/)\n\n[Contact](https:\/\/fastdatascience.com\/contact\/)\n\n[Contact](https:\/\/fastdatascience.com\/contact\/)\n\nEn\n\n- [De](https:\/\/fastdatascience.com\/de\/verarbeitung-nat%C3%BCrlicher-sprache\/experte-f%C3%BCr-nat%C3%BCrliche-sprachverarbeitung\/)\n# Natural Language Processing Expert\n## Natural Language Processing Expert Explains:\nIf your company has a large number of unstructured documents such as CVs, inspection reports, health records, or otherwise, and you are struggling to extract value from them, you could be sitting on a gold mine of data and it might be time to call in a [Natural Language Processing](https:\/\/fastdatascience.com\/natural-language-processing\/) expert. Or maybe your organisation needs to build a chatbot, or analyse and triage emails? In any case our company of NLP experts Fast Data Science can help.\n\n[What is Natural Language Processing](https:\/\/fastdatascience.com\/natural-language-processing\/what-is-nlp\/) (NLP)? NLP is a discipline within artificial intelligence dealing with analysis of human language. With NLP we can interpret documents written by humans, for humans. NLP also includes natural language dialogue systems such as Siri on the iPhone, as well as speech recognition and speech synthesis systems, and search engines! So you might be using NLP systems every day without realising.\n\n[Natural language processing](https:\/\/en.wikipedia.org\/wiki\/Natural_language_processing) has its roots in the 1950s. Already in 1950, [Alan Turing](https:\/\/en.wikipedia.org\/wiki\/Alan_Turing) published an article titled “Computing Machinery and Intelligence” which proposed what is now called the Turing test as a criterion of [intelligence](https:\/\/fastdatascience.com\/)\/, a task that involves the automated interpretation and generation of natural language (e.g. “We are searching in the database”), but at the time not articulated as a problem separate from artificial intelligence.\n\n![NLP expert](https:\/\/fastdatascience.com\/images\/NLP-expert.jpg)\n\n## Natural Language Processing Experts Fast Data Science\nAt Fast Data Science we take pride in our [natural language processing](https:\/\/en.wikipedia.org\/wiki\/Natural_language_processing) expertise (NLP). We offer expertise in many areas of data science and our main area of focus is NLP. The manager, Thomas Wood, studied a Masters in 2008 at Cambridge University in [Computer Speech, Text and Internet Technology](https:\/\/www.cl.cam.ac.uk\/admissions\/cstit\/) and since then he has been working exclusively in machine learning and mostly in NLP. In 2018 he founded Fast Data Science to deliver data science expertise, focusing on NLP. You can read the bios of Thomas Wood and the other Natural Language Processing Experts in our team on the [team page](https:\/\/fastdatascience.com\/team\/). In addition to building NLP pipelines from scratch, our team has worked on [natural language dialogue systems](https:\/\/www.artificial-solutions.com\/), document classifiers and text based recommender systems. For these tasks, we have used both traditional machine learning techniques as well as the state of the art such as deep learning, convolutional neural networks, [BERT](https:\/\/towardsdatascience.com\/bert-explained-state-of-the-art-language-model-for-nlp-f8b21a9b6270), and the like. You can read a post about transformers (the current cutting-edge NLP model) by Thomas Wood on deepai.org [here](https:\/\/deepai.org\/machine-learning-glossary-and-terms\/transformer-neural-network). Our NLP experts normally use [Python](https:\/\/www.python.org\/) but we can adapt to your organisation’s preferred technology stack.\n\nFast Data Science - London\n\n## Need a business solution?\nNLP, ML and data science leader since 2016 - get in touch for an NLP brainstorming session.\n\n[Contact us](https:\/\/fastdatascience.com\/contact\/)\n\n## Our NLP Expertise\nAs a company of Natural Language Experts, we work in all areas of NLP, and are happy to discuss your NLP problem with you. Our NLP expertise includes:\n\n- Natural language understanding\n- Text analysis\n- Topic analysis – clustering, unsupervised learning\n- Document classification\n- Document-based recommender systems\n- Unstructured data analysis\n- Document anonymisation - for example replacing names and addresses with fake entities, this is an ever-expanding need of businesses in the post-GDPR and HIPAA world.\n\n![An NLP Expert can deliver a variety of results for your business](https:\/\/fastdatascience.com\/images\/NLP_expert-min.jpg)*An NLP Expert can deliver a variety of results for your business*\n\n## Experts in NLP and unstructured data\nToday many companies, in particular in certain industries such as healthcare, pharmaceuticals, legal, and insurance, have large amounts of unstructured data. This is typically data in text format, which may even be unscanned documents, PDFs, HTML, or any other file type.\n\nUnstructured data is very difficult to deal with but can contain a goldmine of information. Fast Data Science specialises in extracting value from organisations’ unstructured datasets.\n\n## Natural Language Processing applications in healthcare\n![Natural Language Processing applications in healthcare](https:\/\/fastdatascience.com\/images\/emr1-min_hu8297197299259954454.png) ![Natural Language Processing applications in healthcare](https:\/\/fastdatascience.com\/images\/emr2-min_hu6034424342831273309.png)\n\nAI and natural language processing are being increasingly adopted across the healthcare sector.\n\nThis technology is sometimes called healthtech or MedTech. NLP is being [used](https:\/\/fastdatascience.com\/natural-language-processing\/what-is-nlp-used-for) to compare and detect changes in clinical reports, extract clinical concepts such as MeSH terms from electronic medical records, and develop human-to-machine natural language dialogue systems to improve the healthcare experience.\n\nWe have worked on a number of projects in healthcare, including:\n\n- a [model to predict the complexity of clinical trials](https:\/\/fastdatascience.com\/ai-in-pharma\/clinical-trials-analysis\/) from the trial protocol for [Boehringer Ingelheim](https:\/\/www.boehringer-ingelheim.com\/).\n- a [desktop application](https:\/\/fastdatascience.com\/ai-in-pharma\/pubmed-authorship-analysis) to analyse researchers’ outputs, fields, collaborations and affiliations using [PubMed](https:\/\/pubmed.ncbi.nlm.nih.gov\/) search result exports.\n- a [model to identify researchers](https:\/\/fastdatascience.com\/ai-in-pharma\/finding-molecules-and-proteins-in-scientific-literature) who have used open sourced molecules in their published research without attribution, also for [Boehringer Ingelheim](https:\/\/www.boehringer-ingelheim.com\/).\n## Natural Language Processing technologies at Fast Data Science\nAs NLP experts, we do a lot of natural language processing with Python. We have worked on a variety of NLP models, including:\n\n- Bag of words, tf\\*idf, cosine similarity\n- NLP pipelines, lemmatisation, parsers, chunkers\n- Deep neural networks\n  - convolutional neural networks (text as well as images)\n  - RNN, LSTM\n  - Seq2seq, word2vec, doc2vec\n  - [see a live demo of a CNN for author identification](https:\/\/fastdatascience.com\/natural-language-processing\/forensic-stylometry-linguistics-authorship-analysis\/)\n- Clustering: Latent Dirichlet Allocation\n  - This is useful for extracting topics from a set of unstructured documents, for example legal documents, survey responses, factory error reports, etc.\n- Search engines and search term recommenders\n- Google Natural Language, AWS, Microsoft Azure\n\n![Topic detection is an NLP technique that allows you to discover common themes in a set of unstructured documents.](https:\/\/fastdatascience.com\/images\/carrot2-min.jpg)*Topic detection is an NLP technique that allows you to discover common themes in a set of unstructured documents.*\n\n## Natural Language Processing in Python and R\nWe work with the following programming languages and frameworks:\n\n- TensorFlow\n- Keras\n- Python NLTK\n- R\n\n## Examples of past Natural Language Processing projects\nNLP projects we have worked on for major household names include\n\n- a spoken dialogue system to control a smart home\n- an unsupervised text analysis program to analyse text descriptions of manufacturing defects ([Boehringer Ingelheim](https:\/\/www.boehringer-ingelheim.co.uk\/))\n- a model to classify jobseekers’ CVs into industries and salary bands ([CV-Library](https:\/\/www.cv-library.co.uk\/)).\n- analysis of survey responses ([White Ribbon Alliance](https:\/\/www.whiteribbonalliance.org\/))\n\nWhat we can do for you\n\n## Transform Unstructured Data into Actionable Insights\n\n[Contact us](https:\/\/fastdatascience.com\/contact\/)\n\nHello! How can I assist you today?\n\n## Footer\n[![Fast Data Science®](https:\/\/fastdatascience.com\/images\/logo-light.svg)](https:\/\/fastdatascience.com\/)\n\n### Services\n- [AI for healthcare](https:\/\/fastdatascience.com\/ai-in-healthcare\/)\n- [AI in pharma](https:\/\/fastdatascience.com\/ai-in-pharma\/)\n- [AI in public sector procurement](https:\/\/fastdatascience.com\/public-sector-procurement\/)\n- [AI technical due diligence](https:\/\/fastdatascience.com\/ai-due-diligence\/)\n\n### Skills\n- [Natural Language Processing](https:\/\/fastdatascience.com\/natural-language-processing\/)\n- [Cloud Machine Learning Consulting](https:\/\/fastdatascience.com\/ai-for-business\/cloud-machine-learning-consulting\/)\n- [Predictive Analytics Consulting](https:\/\/fastdatascience.com\/data-science-consulting\/predictive-analytics-consulting\/)\n- [Conversion Optimisation](https:\/\/fastdatascience.com\/ai-for-business\/conversion-optimisation\/)\n- [AI consultancy](https:\/\/fastdatascience.com\/ai-consultancy\/)\n- [AI consultants](https:\/\/fastdatascience.com\/ai-consultant\/)\n\n### Case Studies\n- [Drug named entity recognition Python library](https:\/\/fastdatascience.com\/ai-in-pharma\/drug-named-entity-recognition-python-library\/)\n- [Open Source Tools for Natural Language Processing](https:\/\/fastdatascience.com\/natural-language-processing\/open-source-nlp\/)\n- [Pharma - PubMed authorship analysis](https:\/\/fastdatascience.com\/pubmed-authorship-analysis\/)\n- [Tesco - Customer basket weights](https:\/\/fastdatascience.com\/tesco-customer-basket-weights\/)\n\n### Demos\n- [Clinical Trial Risk Tool](https:\/\/clinicaltrialrisk.org\/tool\/login?guest=true)\n- [NLP Survey Dashboard for What Women Want](https:\/\/whatwomenwant.whiteribbonalliance.org\/)\n- [Harmony](https:\/\/harmonydata.ac.uk\/app)\n- [Author prediction demo](https:\/\/fastdatascience.com\/natural-language-processing\/forensic-stylometry-linguistics-authorship-analysis\/)\n- [Insolvency bot](https:\/\/fastdatascience.com\/insolvency\/)\n\n### About\n- [Team](https:\/\/fastdatascience.com\/team\/)\n- [Blog](https:\/\/fastdatascience.com\/blog\/)\n- [Resources](https:\/\/fastdatascience.com\/resources\/)\n- [Contact](https:\/\/fastdatascience.com\/contact\/)\n- [Company info](https:\/\/fastdatascience.com\/fast-data-science-company\/)\n- [Privacy policy](https:\/\/fastdatascience.com\/privacy-policy\/)\n- [Publications and patents](https:\/\/fastdatascience.com\/publications-and-patents\/)\n- [Frequently Asked Questions](https:\/\/fastdatascience.com\/faq\/)\n\n[Twitter](https:\/\/twitter.com\/fastdatascienc1)\n\n[Facebook](https:\/\/www.facebook.com\/fastdatascienceltd\/)\n\n[Linkedin](https:\/\/www.linkedin.com\/company\/fastdatascience\/)\n\n[youtube](https:\/\/www.youtube.com\/channel\/UCLPrDH7SoRT55F6i50xMg5g)\n\n[tumblr](https:\/\/fastdatascience.tumblr.com\/)\n\n[GitHub](https:\/\/github.com\/fastdatascience)\n\n[Google](https:\/\/g.page\/fast-data-science)\n\n[instagram](https:\/\/www.instagram.com\/fastdatascience)\n\n[threads](https:\/\/www.threads.net\/@fastdatascience)\n\n[yelp](https:\/\/www.yelp.com\/biz\/fast-data-science-london)\n\n[mastodon](https:\/\/mastodon.social\/@fastdatascience)\n\n[Bluesky](https:\/\/bsky.app\/profile\/fastdatascience.bsky.social)\n\n[Subscribe on LinkedIn](https:\/\/www.linkedin.com\/build-relation\/newsletter-follow?entityUrn=7213853581227999232)\n\n© 2026 Fast Data Science Ltd, provider of natural language processing, machine learning and data science consulting services, London, U.K Director: Thomas Wood. Fast Data Science® is a registered trademark of Fast Data Science Ltd.","attrs_readable_markdown":"## Natural Language Processing Expert Explains:\nIf your company has a large number of unstructured documents such as CVs, inspection reports, health records, or otherwise, and you are struggling to extract value from them, you could be sitting on a gold mine of data and it might be time to call in a [Natural Language Processing](https:\/\/fastdatascience.com\/natural-language-processing\/) expert. Or maybe your organisation needs to build a chatbot, or analyse and triage emails? In any case our company of NLP experts Fast Data Science can help.\n\n[What is Natural Language Processing](https:\/\/fastdatascience.com\/natural-language-processing\/what-is-nlp\/) (NLP)? NLP is a discipline within artificial intelligence dealing with analysis of human language. With NLP we can interpret documents written by humans, for humans. NLP also includes natural language dialogue systems such as Siri on the iPhone, as well as speech recognition and speech synthesis systems, and search engines! So you might be using NLP systems every day without realising.\n\n[Natural language processing](https:\/\/en.wikipedia.org\/wiki\/Natural_language_processing) has its roots in the 1950s. Already in 1950, [Alan Turing](https:\/\/en.wikipedia.org\/wiki\/Alan_Turing) published an article titled “Computing Machinery and Intelligence” which proposed what is now called the Turing test as a criterion of [intelligence](https:\/\/fastdatascience.com\/)\/, a task that involves the automated interpretation and generation of natural language (e.g. “We are searching in the database”), but at the time not articulated as a problem separate from artificial intelligence.\n\n![NLP expert](https:\/\/fastdatascience.com\/images\/NLP-expert.jpg)\n\n## Natural Language Processing Experts Fast Data Science\nAt Fast Data Science we take pride in our [natural language processing](https:\/\/en.wikipedia.org\/wiki\/Natural_language_processing) expertise (NLP). We offer expertise in many areas of data science and our main area of focus is NLP. The manager, Thomas Wood, studied a Masters in 2008 at Cambridge University in [Computer Speech, Text and Internet Technology](https:\/\/www.cl.cam.ac.uk\/admissions\/cstit\/) and since then he has been working exclusively in machine learning and mostly in NLP. In 2018 he founded Fast Data Science to deliver data science expertise, focusing on NLP. You can read the bios of Thomas Wood and the other Natural Language Processing Experts in our team on the [team page](https:\/\/fastdatascience.com\/team\/). In addition to building NLP pipelines from scratch, our team has worked on [natural language dialogue systems](https:\/\/www.artificial-solutions.com\/), document classifiers and text based recommender systems. For these tasks, we have used both traditional machine learning techniques as well as the state of the art such as deep learning, convolutional neural networks, [BERT](https:\/\/towardsdatascience.com\/bert-explained-state-of-the-art-language-model-for-nlp-f8b21a9b6270), and the like. You can read a post about transformers (the current cutting-edge NLP model) by Thomas Wood on deepai.org [here](https:\/\/deepai.org\/machine-learning-glossary-and-terms\/transformer-neural-network). Our NLP experts normally use [Python](https:\/\/www.python.org\/) but we can adapt to your organisation’s preferred technology stack.\n\nFast Data Science - London\n\n## Need a business solution?\nNLP, ML and data science leader since 2016 - get in touch for an NLP brainstorming session.\n\n## Our NLP Expertise\nAs a company of Natural Language Experts, we work in all areas of NLP, and are happy to discuss your NLP problem with you. Our NLP expertise includes:\n\n- Natural language understanding\n- Text analysis\n- Topic analysis – clustering, unsupervised learning\n- Document classification\n- Document-based recommender systems\n- Unstructured data analysis\n- Document anonymisation - for example replacing names and addresses with fake entities, this is an ever-expanding need of businesses in the post-GDPR and HIPAA world.\n\n![An NLP Expert can deliver a variety of results for your business](https:\/\/fastdatascience.com\/images\/NLP_expert-min.jpg)*An NLP Expert can deliver a variety of results for your business*\n\n## Experts in NLP and unstructured data\nToday many companies, in particular in certain industries such as healthcare, pharmaceuticals, legal, and insurance, have large amounts of unstructured data. This is typically data in text format, which may even be unscanned documents, PDFs, HTML, or any other file type.\n\nUnstructured data is very difficult to deal with but can contain a goldmine of information. Fast Data Science specialises in extracting value from organisations’ unstructured datasets.\n\n## Natural Language Processing applications in healthcare\n![Natural Language Processing applications in healthcare](https:\/\/fastdatascience.com\/images\/emr1-min_hu8297197299259954454.png) ![Natural Language Processing applications in healthcare](https:\/\/fastdatascience.com\/images\/emr2-min_hu6034424342831273309.png)\n\nAI and natural language processing are being increasingly adopted across the healthcare sector.\n\nThis technology is sometimes called healthtech or MedTech. NLP is being [used](https:\/\/fastdatascience.com\/natural-language-processing\/what-is-nlp-used-for) to compare and detect changes in clinical reports, extract clinical concepts such as MeSH terms from electronic medical records, and develop human-to-machine natural language dialogue systems to improve the healthcare experience.\n## Natural Language Processing technologies at Fast Data Science\nAs NLP experts, we do a lot of natural language processing with Python. We have worked on a variety of NLP models, including:\n\n- Bag of words, tf\\*idf, cosine similarity\n- NLP pipelines, lemmatisation, parsers, chunkers\n- Deep neural networks\n  - convolutional neural networks (text as well as images)\n  - RNN, LSTM\n  - Seq2seq, word2vec, doc2vec\n  - [see a live demo of a CNN for author identification](https:\/\/fastdatascience.com\/natural-language-processing\/forensic-stylometry-linguistics-authorship-analysis\/)\n- Clustering: Latent Dirichlet Allocation\n  - This is useful for extracting topics from a set of unstructured documents, for example legal documents, survey responses, factory error reports, etc.\n- Search engines and search term recommenders\n- Google Natural Language, AWS, Microsoft Azure\n\n![Topic detection is an NLP technique that allows you to discover common themes in a set of unstructured documents.](https:\/\/fastdatascience.com\/images\/carrot2-min.jpg)*Topic detection is an NLP technique that allows you to discover common themes in a set of unstructured documents.*\n\n## Natural Language Processing in Python and R\nWe work with the following programming languages and frameworks:\n\n- TensorFlow\n- Keras\n- Python NLTK\n- R\n\n## Examples of past Natural Language Processing projects\nNLP projects we have worked on for major household names include\n\n- a spoken dialogue system to control a smart home\n- an unsupervised text analysis program to analyse text descriptions of manufacturing defects ([Boehringer Ingelheim](https:\/\/www.boehringer-ingelheim.co.uk\/))\n- a model to classify jobseekers’ CVs into industries and salary bands ([CV-Library](https:\/\/www.cv-library.co.uk\/)).\n- analysis of survey responses ([White Ribbon Alliance](https:\/\/www.whiteribbonalliance.org\/))","meta_canonical":null}

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Meta Description	Natural Language Processing Expert Explains: If your company has a large number of unstructured documents such as CVs, inspection reports, health records, or otherwise, and you are struggling to extract value from them, you could be sitting on a gold mine of data and it might be time to call in a Natural Language Processing expert. Or maybe your organisation needs to build a chatbot, or analyse and triage emails? In any case our company of NLP experts Fast Data Science can help.
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Boilerpipe Text	Natural Language Processing Expert Explains: If your company has a large number of unstructured documents such as CVs, inspection reports, health records, or otherwise, and you are struggling to extract value from them, you could be sitting on a gold mine of data and it might be time to call in a Natural Language Processing expert. Or maybe your organisation needs to build a chatbot, or analyse and triage emails? In any case our company of NLP experts Fast Data Science can help. What is Natural Language Processing (NLP)? NLP is a discipline within artificial intelligence dealing with analysis of human language. With NLP we can interpret documents written by humans, for humans. NLP also includes natural language dialogue systems such as Siri on the iPhone, as well as speech recognition and speech synthesis systems, and search engines! So you might be using NLP systems every day without realising. Natural language processing has its roots in the 1950s. Already in 1950, Alan Turing published an article titled “Computing Machinery and Intelligence” which proposed what is now called the Turing test as a criterion of intelligence /, a task that involves the automated interpretation and generation of natural language (e.g. “We are searching in the database”), but at the time not articulated as a problem separate from artificial intelligence. Natural Language Processing Experts Fast Data Science At Fast Data Science we take pride in our natural language processing expertise (NLP). We offer expertise in many areas of data science and our main area of focus is NLP. The manager, Thomas Wood, studied a Masters in 2008 at Cambridge University in Computer Speech, Text and Internet Technology and since then he has been working exclusively in machine learning and mostly in NLP. In 2018 he founded Fast Data Science to deliver data science expertise, focusing on NLP. You can read the bios of Thomas Wood and the other Natural Language Processing Experts in our team on the team page . In addition to building NLP pipelines from scratch, our team has worked on natural language dialogue systems , document classifiers and text based recommender systems. For these tasks, we have used both traditional machine learning techniques as well as the state of the art such as deep learning, convolutional neural networks, BERT , and the like. You can read a post about transformers (the current cutting-edge NLP model) by Thomas Wood on deepai.org here . Our NLP experts normally use Python but we can adapt to your organisation’s preferred technology stack. Fast Data Science - London Need a business solution? NLP, ML and data science leader since 2016 - get in touch for an NLP brainstorming session. Our NLP Expertise As a company of Natural Language Experts, we work in all areas of NLP, and are happy to discuss your NLP problem with you. Our NLP expertise includes: Natural language understanding Text analysis Topic analysis – clustering, unsupervised learning Document classification Document-based recommender systems Unstructured data analysis Document anonymisation - for example replacing names and addresses with fake entities, this is an ever-expanding need of businesses in the post-GDPR and HIPAA world. An NLP Expert can deliver a variety of results for your business Experts in NLP and unstructured data Today many companies, in particular in certain industries such as healthcare, pharmaceuticals, legal, and insurance, have large amounts of unstructured data. This is typically data in text format, which may even be unscanned documents, PDFs, HTML, or any other file type. Unstructured data is very difficult to deal with but can contain a goldmine of information. Fast Data Science specialises in extracting value from organisations’ unstructured datasets. Natural Language Processing applications in healthcare AI and natural language processing are being increasingly adopted across the healthcare sector. This technology is sometimes called healthtech or MedTech. NLP is being used to compare and detect changes in clinical reports, extract clinical concepts such as MeSH terms from electronic medical records, and develop human-to-machine natural language dialogue systems to improve the healthcare experience. Natural Language Processing technologies at Fast Data Science As NLP experts, we do a lot of natural language processing with Python. We have worked on a variety of NLP models, including: Bag of words, tf*idf, cosine similarity NLP pipelines, lemmatisation, parsers, chunkers Deep neural networks convolutional neural networks (text as well as images) RNN, LSTM Seq2seq, word2vec, doc2vec see a live demo of a CNN for author identification Clustering: Latent Dirichlet Allocation This is useful for extracting topics from a set of unstructured documents, for example legal documents, survey responses, factory error reports, etc. Search engines and search term recommenders Google Natural Language, AWS, Microsoft Azure Topic detection is an NLP technique that allows you to discover common themes in a set of unstructured documents. Natural Language Processing in Python and R We work with the following programming languages and frameworks: TensorFlow Keras Python NLTK R Examples of past Natural Language Processing projects NLP projects we have worked on for major household names include a spoken dialogue system to control a smart home an unsupervised text analysis program to analyse text descriptions of manufacturing defects ( Boehringer Ingelheim ) a model to classify jobseekers’ CVs into industries and salary bands ( CV-Library ). analysis of survey responses ( White Ribbon Alliance )
Markdown	[Fast Data Science® ![Fast Data Science®](https://fastdatascience.com/images/logo.svg)](https://fastdatascience.com/) Toggle main menu Services [Data science services overview](https://fastdatascience.com/services/) [Machine learning hands-on development](https://fastdatascience.com/data-science-consulting/machine-learning-consulting/) [AI strategy consulting](https://fastdatascience.com/ai-for-business/ai-strategy-consulting/) [Fractional head of AI](https://fastdatascience.com/ai-for-business/fractional-head-of-ai/) [Technical due diligence on AI companies](https://fastdatascience.com/ai-due-diligence/) [Training courses and workshops](https://fastdatascience.com/training-and-upskilling-analytics-teams-in-data-science/) Tools [Clinical Trial Risk Tool](https://fastdatascience.com/ai-in-pharma/clinical-trial-risk-tool/) [NLP dashboard](https://fastdatascience.com/natural-language-processing/nlp-dashboard/) [Harmony (data harmonisation)](https://fastdatascience.com/ai-in-research/harmony-wellcome-data-prize/) [Drug Names Plugin](https://fastdatascience.com/ai-in-pharma/drug-name-recogniser/) [UK Company Details plugin](https://fastdatascience.com/uk-company-details/) [Company name recognition](https://fastdatascience.com/natural-language-processing/company-named-entity-recognition/) [Author identification](https://fastdatascience.com/natural-language-processing/forensic-stylometry-linguistics-authorship-analysis/) [Insolvency Bot (legal Q\&A)](https://fastdatascience.com/insolvency/) Skills [Skills overview](https://fastdatascience.com/skills/) [Natural language processing](https://fastdatascience.com/natural-language-processing/) [Cloud machine learning](https://fastdatascience.com/ai-for-business/cloud-machine-learning-consulting/) [Predictive analytics](https://fastdatascience.com/data-science-consulting/predictive-analytics-consulting/) [Conversion optimisation](https://fastdatascience.com/ai-for-business/conversion-optimisation/) [Deep learning](https://fastdatascience.com/data-science-consulting/deep-learning-consulting/) [Case studies](https://fastdatascience.com/case-studies/) [Blog](https://fastdatascience.com/blog/) About [Team](https://fastdatascience.com/team/) [Resources](https://fastdatascience.com/resources/) [Company info](https://fastdatascience.com/fast-data-science-company/) [Contact](https://fastdatascience.com/contact/) En - 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[De](https://fastdatascience.com/de/verarbeitung-nat%C3%BCrlicher-sprache/experte-f%C3%BCr-nat%C3%BCrliche-sprachverarbeitung/) # Natural Language Processing Expert ## Natural Language Processing Expert Explains: If your company has a large number of unstructured documents such as CVs, inspection reports, health records, or otherwise, and you are struggling to extract value from them, you could be sitting on a gold mine of data and it might be time to call in a [Natural Language Processing](https://fastdatascience.com/natural-language-processing/) expert. Or maybe your organisation needs to build a chatbot, or analyse and triage emails? In any case our company of NLP experts Fast Data Science can help. [What is Natural Language Processing](https://fastdatascience.com/natural-language-processing/what-is-nlp/) (NLP)? NLP is a discipline within artificial intelligence dealing with analysis of human language. With NLP we can interpret documents written by humans, for humans. NLP also includes natural language dialogue systems such as Siri on the iPhone, as well as speech recognition and speech synthesis systems, and search engines! So you might be using NLP systems every day without realising. [Natural language processing](https://en.wikipedia.org/wiki/Natural_language_processing) has its roots in the 1950s. Already in 1950, [Alan Turing](https://en.wikipedia.org/wiki/Alan_Turing) published an article titled “Computing Machinery and Intelligence” which proposed what is now called the Turing test as a criterion of [intelligence](https://fastdatascience.com/)/, a task that involves the automated interpretation and generation of natural language (e.g. “We are searching in the database”), but at the time not articulated as a problem separate from artificial intelligence. ![NLP expert](https://fastdatascience.com/images/NLP-expert.jpg) ## Natural Language Processing Experts Fast Data Science At Fast Data Science we take pride in our [natural language processing](https://en.wikipedia.org/wiki/Natural_language_processing) expertise (NLP). We offer expertise in many areas of data science and our main area of focus is NLP. The manager, Thomas Wood, studied a Masters in 2008 at Cambridge University in [Computer Speech, Text and Internet Technology](https://www.cl.cam.ac.uk/admissions/cstit/) and since then he has been working exclusively in machine learning and mostly in NLP. In 2018 he founded Fast Data Science to deliver data science expertise, focusing on NLP. You can read the bios of Thomas Wood and the other Natural Language Processing Experts in our team on the [team page](https://fastdatascience.com/team/). In addition to building NLP pipelines from scratch, our team has worked on [natural language dialogue systems](https://www.artificial-solutions.com/), document classifiers and text based recommender systems. For these tasks, we have used both traditional machine learning techniques as well as the state of the art such as deep learning, convolutional neural networks, [BERT](https://towardsdatascience.com/bert-explained-state-of-the-art-language-model-for-nlp-f8b21a9b6270), and the like. You can read a post about transformers (the current cutting-edge NLP model) by Thomas Wood on deepai.org [here](https://deepai.org/machine-learning-glossary-and-terms/transformer-neural-network). Our NLP experts normally use [Python](https://www.python.org/) but we can adapt to your organisation’s preferred technology stack. Fast Data Science - London ## Need a business solution? NLP, ML and data science leader since 2016 - get in touch for an NLP brainstorming session. [Contact us](https://fastdatascience.com/contact/) ## Our NLP Expertise As a company of Natural Language Experts, we work in all areas of NLP, and are happy to discuss your NLP problem with you. Our NLP expertise includes: - Natural language understanding - Text analysis - Topic analysis – clustering, unsupervised learning - Document classification - Document-based recommender systems - Unstructured data analysis - Document anonymisation - for example replacing names and addresses with fake entities, this is an ever-expanding need of businesses in the post-GDPR and HIPAA world. ![An NLP Expert can deliver a variety of results for your business](https://fastdatascience.com/images/NLP_expert-min.jpg)An NLP Expert can deliver a variety of results for your business ## Experts in NLP and unstructured data Today many companies, in particular in certain industries such as healthcare, pharmaceuticals, legal, and insurance, have large amounts of unstructured data. This is typically data in text format, which may even be unscanned documents, PDFs, HTML, or any other file type. Unstructured data is very difficult to deal with but can contain a goldmine of information. Fast Data Science specialises in extracting value from organisations’ unstructured datasets. ## Natural Language Processing applications in healthcare ![Natural Language Processing applications in healthcare](https://fastdatascience.com/images/emr1-min_hu8297197299259954454.png) ![Natural Language Processing applications in healthcare](https://fastdatascience.com/images/emr2-min_hu6034424342831273309.png) AI and natural language processing are being increasingly adopted across the healthcare sector. This technology is sometimes called healthtech or MedTech. NLP is being [used](https://fastdatascience.com/natural-language-processing/what-is-nlp-used-for) to compare and detect changes in clinical reports, extract clinical concepts such as MeSH terms from electronic medical records, and develop human-to-machine natural language dialogue systems to improve the healthcare experience. We have worked on a number of projects in healthcare, including: - a [model to predict the complexity of clinical trials](https://fastdatascience.com/ai-in-pharma/clinical-trials-analysis/) from the trial protocol for [Boehringer Ingelheim](https://www.boehringer-ingelheim.com/). - a [desktop application](https://fastdatascience.com/ai-in-pharma/pubmed-authorship-analysis) to analyse researchers’ outputs, fields, collaborations and affiliations using [PubMed](https://pubmed.ncbi.nlm.nih.gov/) search result exports. - a [model to identify researchers](https://fastdatascience.com/ai-in-pharma/finding-molecules-and-proteins-in-scientific-literature) who have used open sourced molecules in their published research without attribution, also for [Boehringer Ingelheim](https://www.boehringer-ingelheim.com/). ## Natural Language Processing technologies at Fast Data Science As NLP experts, we do a lot of natural language processing with Python. We have worked on a variety of NLP models, including: - Bag of words, tf\idf, cosine similarity - NLP pipelines, lemmatisation, parsers, chunkers - Deep neural networks - convolutional neural networks (text as well as images) - RNN, LSTM - Seq2seq, word2vec, doc2vec - [see a live demo of a CNN for author identification](https://fastdatascience.com/natural-language-processing/forensic-stylometry-linguistics-authorship-analysis/) - Clustering: Latent Dirichlet Allocation - This is useful for extracting topics from a set of unstructured documents, for example legal documents, survey responses, factory error reports, etc. - Search engines and search term recommenders - Google Natural Language, AWS, Microsoft Azure ![Topic detection is an NLP technique that allows you to discover common themes in a set of unstructured documents.](https://fastdatascience.com/images/carrot2-min.jpg)Topic detection is an NLP technique that allows you to discover common themes in a set of unstructured documents.* ## Natural Language Processing in Python and R We work with the following programming languages and frameworks: - TensorFlow - Keras - Python NLTK - R ## Examples of past Natural Language Processing projects NLP projects we have worked on for major household names include - a spoken dialogue system to control a smart home - an unsupervised text analysis program to analyse text descriptions of manufacturing defects ([Boehringer Ingelheim](https://www.boehringer-ingelheim.co.uk/)) - a model to classify jobseekers’ CVs into industries and salary bands ([CV-Library](https://www.cv-library.co.uk/)). - analysis of survey responses ([White Ribbon Alliance](https://www.whiteribbonalliance.org/)) What we can do for you ## Transform Unstructured Data into Actionable Insights [Contact us](https://fastdatascience.com/contact/) Hello! How can I assist you today? ## Footer [![Fast Data Science®](https://fastdatascience.com/images/logo-light.svg)](https://fastdatascience.com/) ### Services - [AI for healthcare](https://fastdatascience.com/ai-in-healthcare/) - [AI in pharma](https://fastdatascience.com/ai-in-pharma/) - [AI in public sector procurement](https://fastdatascience.com/public-sector-procurement/) - [AI technical due diligence](https://fastdatascience.com/ai-due-diligence/) ### Skills - [Natural Language Processing](https://fastdatascience.com/natural-language-processing/) - [Cloud Machine Learning Consulting](https://fastdatascience.com/ai-for-business/cloud-machine-learning-consulting/) - [Predictive Analytics Consulting](https://fastdatascience.com/data-science-consulting/predictive-analytics-consulting/) - [Conversion Optimisation](https://fastdatascience.com/ai-for-business/conversion-optimisation/) - [AI consultancy](https://fastdatascience.com/ai-consultancy/) - [AI consultants](https://fastdatascience.com/ai-consultant/) ### Case Studies - [Drug named entity recognition Python library](https://fastdatascience.com/ai-in-pharma/drug-named-entity-recognition-python-library/) - [Open Source Tools for Natural Language Processing](https://fastdatascience.com/natural-language-processing/open-source-nlp/) - [Pharma - PubMed authorship analysis](https://fastdatascience.com/pubmed-authorship-analysis/) - [Tesco - Customer basket weights](https://fastdatascience.com/tesco-customer-basket-weights/) ### Demos - [Clinical Trial Risk Tool](https://clinicaltrialrisk.org/tool/login?guest=true) - [NLP Survey Dashboard for What Women Want](https://whatwomenwant.whiteribbonalliance.org/) - [Harmony](https://harmonydata.ac.uk/app) - [Author prediction demo](https://fastdatascience.com/natural-language-processing/forensic-stylometry-linguistics-authorship-analysis/) - [Insolvency bot](https://fastdatascience.com/insolvency/) ### About - [Team](https://fastdatascience.com/team/) - [Blog](https://fastdatascience.com/blog/) - [Resources](https://fastdatascience.com/resources/) - [Contact](https://fastdatascience.com/contact/) - [Company info](https://fastdatascience.com/fast-data-science-company/) - [Privacy policy](https://fastdatascience.com/privacy-policy/) - [Publications and patents](https://fastdatascience.com/publications-and-patents/) - [Frequently Asked Questions](https://fastdatascience.com/faq/) [Twitter](https://twitter.com/fastdatascienc1) [Facebook](https://www.facebook.com/fastdatascienceltd/) [Linkedin](https://www.linkedin.com/company/fastdatascience/) [youtube](https://www.youtube.com/channel/UCLPrDH7SoRT55F6i50xMg5g) [tumblr](https://fastdatascience.tumblr.com/) [GitHub](https://github.com/fastdatascience) [Google](https://g.page/fast-data-science) [instagram](https://www.instagram.com/fastdatascience) [threads](https://www.threads.net/@fastdatascience) [yelp](https://www.yelp.com/biz/fast-data-science-london) [mastodon](https://mastodon.social/@fastdatascience) [Bluesky](https://bsky.app/profile/fastdatascience.bsky.social) [Subscribe on LinkedIn](https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7213853581227999232) © 2026 Fast Data Science Ltd, provider of natural language processing, machine learning and data science consulting services, London, U.K Director: Thomas Wood. 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Readable Markdown	## Natural Language Processing Expert Explains: If your company has a large number of unstructured documents such as CVs, inspection reports, health records, or otherwise, and you are struggling to extract value from them, you could be sitting on a gold mine of data and it might be time to call in a [Natural Language Processing](https://fastdatascience.com/natural-language-processing/) expert. Or maybe your organisation needs to build a chatbot, or analyse and triage emails? In any case our company of NLP experts Fast Data Science can help. [What is Natural Language Processing](https://fastdatascience.com/natural-language-processing/what-is-nlp/) (NLP)? NLP is a discipline within artificial intelligence dealing with analysis of human language. With NLP we can interpret documents written by humans, for humans. NLP also includes natural language dialogue systems such as Siri on the iPhone, as well as speech recognition and speech synthesis systems, and search engines! So you might be using NLP systems every day without realising. [Natural language processing](https://en.wikipedia.org/wiki/Natural_language_processing) has its roots in the 1950s. Already in 1950, [Alan Turing](https://en.wikipedia.org/wiki/Alan_Turing) published an article titled “Computing Machinery and Intelligence” which proposed what is now called the Turing test as a criterion of [intelligence](https://fastdatascience.com/)/, a task that involves the automated interpretation and generation of natural language (e.g. “We are searching in the database”), but at the time not articulated as a problem separate from artificial intelligence. ![NLP expert](https://fastdatascience.com/images/NLP-expert.jpg) ## Natural Language Processing Experts Fast Data Science At Fast Data Science we take pride in our [natural language processing](https://en.wikipedia.org/wiki/Natural_language_processing) expertise (NLP). We offer expertise in many areas of data science and our main area of focus is NLP. The manager, Thomas Wood, studied a Masters in 2008 at Cambridge University in [Computer Speech, Text and Internet Technology](https://www.cl.cam.ac.uk/admissions/cstit/) and since then he has been working exclusively in machine learning and mostly in NLP. In 2018 he founded Fast Data Science to deliver data science expertise, focusing on NLP. You can read the bios of Thomas Wood and the other Natural Language Processing Experts in our team on the [team page](https://fastdatascience.com/team/). In addition to building NLP pipelines from scratch, our team has worked on [natural language dialogue systems](https://www.artificial-solutions.com/), document classifiers and text based recommender systems. For these tasks, we have used both traditional machine learning techniques as well as the state of the art such as deep learning, convolutional neural networks, [BERT](https://towardsdatascience.com/bert-explained-state-of-the-art-language-model-for-nlp-f8b21a9b6270), and the like. You can read a post about transformers (the current cutting-edge NLP model) by Thomas Wood on deepai.org [here](https://deepai.org/machine-learning-glossary-and-terms/transformer-neural-network). Our NLP experts normally use [Python](https://www.python.org/) but we can adapt to your organisation’s preferred technology stack. Fast Data Science - London ## Need a business solution? NLP, ML and data science leader since 2016 - get in touch for an NLP brainstorming session. ## Our NLP Expertise As a company of Natural Language Experts, we work in all areas of NLP, and are happy to discuss your NLP problem with you. Our NLP expertise includes: - Natural language understanding - Text analysis - Topic analysis – clustering, unsupervised learning - Document classification - Document-based recommender systems - Unstructured data analysis - Document anonymisation - for example replacing names and addresses with fake entities, this is an ever-expanding need of businesses in the post-GDPR and HIPAA world. ![An NLP Expert can deliver a variety of results for your business](https://fastdatascience.com/images/NLP_expert-min.jpg)An NLP Expert can deliver a variety of results for your business ## Experts in NLP and unstructured data Today many companies, in particular in certain industries such as healthcare, pharmaceuticals, legal, and insurance, have large amounts of unstructured data. This is typically data in text format, which may even be unscanned documents, PDFs, HTML, or any other file type. Unstructured data is very difficult to deal with but can contain a goldmine of information. Fast Data Science specialises in extracting value from organisations’ unstructured datasets. ## Natural Language Processing applications in healthcare ![Natural Language Processing applications in healthcare](https://fastdatascience.com/images/emr1-min_hu8297197299259954454.png) ![Natural Language Processing applications in healthcare](https://fastdatascience.com/images/emr2-min_hu6034424342831273309.png) AI and natural language processing are being increasingly adopted across the healthcare sector. This technology is sometimes called healthtech or MedTech. NLP is being [used](https://fastdatascience.com/natural-language-processing/what-is-nlp-used-for) to compare and detect changes in clinical reports, extract clinical concepts such as MeSH terms from electronic medical records, and develop human-to-machine natural language dialogue systems to improve the healthcare experience. ## Natural Language Processing technologies at Fast Data Science As NLP experts, we do a lot of natural language processing with Python. We have worked on a variety of NLP models, including: - Bag of words, tf\idf, cosine similarity - NLP pipelines, lemmatisation, parsers, chunkers - Deep neural networks - convolutional neural networks (text as well as images) - RNN, LSTM - Seq2seq, word2vec, doc2vec - [see a live demo of a CNN for author identification](https://fastdatascience.com/natural-language-processing/forensic-stylometry-linguistics-authorship-analysis/) - Clustering: Latent Dirichlet Allocation - This is useful for extracting topics from a set of unstructured documents, for example legal documents, survey responses, factory error reports, etc. - Search engines and search term recommenders - Google Natural Language, AWS, Microsoft Azure ![Topic detection is an NLP technique that allows you to discover common themes in a set of unstructured documents.](https://fastdatascience.com/images/carrot2-min.jpg)Topic detection is an NLP technique that allows you to discover common themes in a set of unstructured documents.* ## Natural Language Processing in Python and R We work with the following programming languages and frameworks: - TensorFlow - Keras - Python NLTK - R ## Examples of past Natural Language Processing projects NLP projects we have worked on for major household names include - a spoken dialogue system to control a smart home - an unsupervised text analysis program to analyse text descriptions of manufacturing defects ([Boehringer Ingelheim](https://www.boehringer-ingelheim.co.uk/)) - a model to classify jobseekers’ CVs into industries and salary bands ([CV-Library](https://www.cv-library.co.uk/)). - analysis of survey responses ([White Ribbon Alliance](https://www.whiteribbonalliance.org/))
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