Natural Language Processing Consultant

A Natural Language Processing Consultant Explains:

Natural language processing allows us to tap into unstructured data, whether that is text, audio, images, or videos.

This allows enterprises to achieve insights, improve analytics and decision making, and even develop predictive models for things like insurance claims, legal outcomes, clinical trial risk, trial costs, jobseeker’s salaries, or manufacturing error reports

Yes, these are all examples of projects we’ve taken on for clients at Fast Data Science! Take a look at our case studies for more examples of NLP projects, and drop us a line if you’re interested in extracting value from your unstructured data.

Natural Language Processing and Text Analysis

At Fast Data Science, our main area of focus is natural language processing (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 consulting and mostly in NLP.

In 2018, he founded Fast Data Science to deliver services as a natural language processing consultant. We have built NLP pipelines from scratch, and worked on business-focused NLP consulting engagements.

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A natural language processing consulting engagement will allow you to extract value from your unstructured data

Natural language processing

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People-first natural language processing consulting

We take a people-first approach to natural language processing consulting, identifying opportunities by talking to stakeholders and VPs within an organisation and categorising the opportunities by organisational and stakeholder impact before investigating the technical side of each opportunity. This keeps us focused on the objective of the NLP consulting engagement: to deliver results for your business. We will often begin an engagement with an MVP (minimum viable product), allowing us to show value to the business as soon as possible.

Depending on what delivers the best and most effective result, we use both traditional machine learning techniques as well as the state of the art such as neural networks, and may even leverage off-the-shelf generative models such as OpenAI’s GPT-4. We frequently use a tech stack with Python, Jupyter Notebook, and FastAPI for deployment, optionally including a big data warehouse such as Apache Spark or BigQuery, and Microsoft Azure, AWS, or Google Cloud, for our natural language processing consulting engagements.

NLP and unstructured data

If your organisation has a large amount of unstructured data, such as text, documents, emails, social media, reviews, reports, interview transcripts, or unscanned documents, NLP can deliver a huge amount of value to you, helping your company analyse and extract value from this unstructured data. Just think about the gold mine of valuable insights you get with data analytics consulting.

It is common in many industries, such as healthcare, pharmaceuticals, legal, and insurance, to have large amounts of unstructured data.

Fast Data Science specialises in extracting value from organisations’ unstructured datasets.

Give us a call or drop us an email today and we can discuss your untapped data.

NLP examples

Examples of applications of natural language processing include:

  • Natural language understanding
  • Natural language dialogue systems (check out our company chatbot on the bottom right of this page!)
  • Text analysis
  • Zero-shot and few-shot learning
  • Topic analysis – clustering
  • Document classification (e.g. email triage)
  • Document-based recommender systems
  • Unstructured data analysis
  • Document anonymisation

The list could go on. In fact, we’ve compiled an A-Z of data science!

Natural Language Processing applications in healthcare

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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.

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

Natural Language Processing technologies at Fast Data Science

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 Consultant 3 Topic detection is an NLP technique that allows you to discover common themes in a set of unstructured documents.

What we can do for you

Transform Unstructured Data into Actionable Insights

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