Natural Language Processing Specialists Fast Data Science

At Fast Data Science we take pride in our natural language processing specialism (NLP). We offer specialist consulting 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 in order to deliver data science consulting, specialising in 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 specialist NLP work.

NLP, Our Speciality

As a company of Natural Language Specialists our skills include:

  • Natural language understanding
  • Natural language dialogue systems
  • Text analysis
  • Topic analysis – clustering
  • Document classification
  • Document-based recommender systems
  • Unstructured data analysis
  • Document anonymisation

Specialists 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. For this kind of problem it’s recommended to bring in an NLP specialist.

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.

Healthcare and Medical Natural Language Processing Specialists

Natural Language Processing applications in healthcare 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. Our speciality area, 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.

We have worked on a number of projects in healthcare, including:

Fast Data Science’s speciality Natural Language Processing technologies

As NLP specialists, 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
  • 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
Natural Language Processing word cloud
NLP specialists will use techniques such as topic detection and unsupervised learning to identify patterns, groups and clusters in unstructured document sets

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)

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