Natural language processing is a subfield of linguistics, sitting on a crossroads with computer science, artificial intelligence and engineering. NLP has been an active field of research since the 1950s. 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”). At that time, NLP was not yet seen as its own separate field of research within or separate from artificial intelligence.
Our main area of research focus is natural language processing (NLP) research. The manager, Thomas Wood, studied a Masters in 2008 at Cambridge University in Computer Speech, Text and Internet Technology, and conducted his NLP research project on pleonastic pronouns. 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 consultancy and research, focusing on NLP. We have built NLP pipelines from scratch, and 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 neural networks. We normally use Python for our NLP research.
Examples of natural language processing research areas include:
Fast Data Science - London
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. If you have a large document set in your organisation, consider hiring a company of NLP researchers such as Fast Data Science.
AI and natural language processing are being increasingly adopted across the healthcare sector.
Healthtech and MedTech are hot areas of NLP research. NLP researchers are using NLP 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. These NLP research breakthroughs are beginning to impact the sector.
We have worked on a number of NLP research projects in healthcare, including:
We do a lot of natural language processing with Python. We have used many NLP models and architectures in our research, including:
We work with the following programming languages and frameworks:
NLP projects we have worked on for major household names include
What we can do for you
