Natural language processing

Fast Data Science webinar on AI and NLP in pharmaceuticals
Ai in pharmaNatural language processing

Fast Data Science webinar on AI and NLP in pharmaceuticals

On 29 May, Thomas Wood presented a webinar on how AI and Natural Language Processing (NLP) can transform clinical trials in the pharmaceutical industry.

Clinical trial cost modelling with NLP and AI
Ai in pharmaNatural language processing

Clinical trial cost modelling with NLP and AI

Modelling risk and cost in clinical trials with NLP Fast Data Science’s Clinical Trial Risk Tool Clinical trials are a vital part of bringing new drugs to market, but planning and running them can be a complex and expensive process.

Semantic similarity with sentence embeddings
Natural language processing

Semantic similarity with sentence embeddings

In natural language processing, we have the concept of word vector embeddings and sentence embeddings. This is a vector, typically hundreds of numbers, which represents the meaning of a word or sentence.

Finance named entity recognition
Ai in financeNatural language processing

Finance named entity recognition

Some finance companies have contacted Fast Data Science with a need for a very customised named entity recognition solution. Clients prepare lists of investments which could be funds or companies, and request a check on those companies.

Business uses of natural language processing - the 2024 capabilities of NLP
Natural language processingAi for business

Business uses of natural language processing - the 2024 capabilities of NLP

What is NLP in business environments? Natural language processing (NLP) is a branch of AI (Artificial Intelligence), empowering computers to not just understand but also process and generate language in the same way that humans do.

Top NLP APIs to use in 2023
Natural language processing

Top NLP APIs to use in 2023

Natural language processing (NLP) is no longer a term that makes people shake their heads and go “huh…?” – on the contrary, most businesses are aware of what it is and the powerful applications it offers through its variety of natural language APIs, text analysis APIs, and text processing APIs.

Detect fake news with natural language processing
Natural language processing

Detect fake news with natural language processing

Can we detect what is fake news or plagiarised in 59 articles for Der Spiegel by Claas Relotius? We used natural language processing to uncover the clues that pointed to a rogue journalist’s history of submitting fake news

Natural language processing capabilities and use cases - the 2023 report
Natural language processing

Natural language processing capabilities and use cases - the 2023 report

NLP use cases have grown significantly in recent years. From NLP use cases in finance to NLP in healthcare use cases, we explore the various uses for business.

The state of Text Analysis in 2024: Trends and Capabilities
Natural language processing

The state of Text Analysis in 2024: Trends and Capabilities

How is text analysis AI looking in 2024, how it generally works, and how you can use it to take your customers, employees, and brand to the next level – all this and more in our in-depth article.

What is Natural Language Understanding (NLU) and how is it used in practice?
Natural language processing

What is Natural Language Understanding (NLU) and how is it used in practice?

Natural Language Understanding (NLU): Overview If we think about it, language is one of the most powerful tools in our arsenal.

Fast Stylometry Python Library
Natural language processing

Fast Stylometry Python Library

Fast Stylometry Tutorial I’m introducing a Python library I’ve written, called faststylometry, which allows you to compare authors of texts by their writing style.

NLP on under-resourced languages
Natural language processing

NLP on under-resourced languages

Image from: harmonydata.ac.uk “Thinking too much” I have been working on the development of Harmony, a tool to help psychology researchers harmonise questionnaire items in plain text across languages so that they can combine datasets from disparate sources.

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