Thomas Wood

Thomas Wood

I am a London-based freelance data scientist, available for consulting engagements especially around NLP (natural language processing). I help organisations extract value from unstructured data. If you have a large amount of text documents (examples include but are not limited to pharmaceutical regulatory documents, legal caseloads, credit reports), and would like to understand how this can benefit your organisation, and even quantify the benefit before getting started, please let me know.

Recent posts by Thomas Wood

 Train your own AI: Fine tune a large language model for sentence similarity

Train your own AI: Fine tune a large language model for sentence similarity

“Fine-tuning” means adapting an existing machine learning model for specific tasks or use cases. In this post I’m going to walk you through how you can fine tune a large language model for sentence similarity using some hand annotated test data. This example is in the psychology domain. You need training data consisting of pairs of sentences, and a “ground truth” of how similar you want those sentences to be when you train your custom sentence similarity model.

Hire an NLP developer
Ai and nlpBusiness applications

Hire an NLP developer

Hire an NLP developer and untangle the power of natural language in your projects The world is buzzing with the possibilities of natural language processing (NLP). From chatbots that understand your needs to algorithms that analyse mountains of text data, NLP is revolutionising industries across the board. But harnessing this power requires the right expertise. That’s where finding the perfect NLP developer comes in. Post a job in NLP on naturallanguageprocessing.

What is NLP?

What is NLP?

Natural language processing What is natural language processing? Natural language processing, or NLP, is a field of artificial intelligence that focuses on the interaction between computers and humans using natural language. NLP is a branch of AI but is really a mixture of disciplines such as linguistics, computer science, and engineering. There are a number of approaches to NLP, ranging from rule-based modelling of human language to statistical methods. Common uses of NLP include speech recognition systems, the voice assistants available on smartphones, and chatbots.

Hire an NLP data scientist
Ai and nlpBusiness applications

Hire an NLP data scientist

Hire an NLP data scientist and boost your business with AI As artificial intelligence transcends the realm of sci-fi and starts getting intricately woven into our everyday lives, the demand for specialized professionals to oversee its many dimensions has never been higher. If your company is looking to step into the future, now is the perfect time to hire an NLP data scientist! What is an NLP data scientist? Natural Language Processing (NLP), a subset of machine learning, focuses on the interaction between humans and computers via natural language.

Unsolved problems in natural language processing

Unsolved problems in natural language processing

Unsolved problems in natural language processing Here’s a walk through of some of NLP’s most intriguing unsolved mysteries. Forensic stylometry Who wrote which parts of the Federalist Papers? Who is Elena Ferrante? Who was S.W. Erdnase, the pseudonymous author of The Expert at the Card Table? Translation Can we make a machine translator as good as a human? Machine translation is an AI-complete problem, requiring an AI to have real-world knowledge to solve properly.

Which NLP corpus?

Which NLP corpus?

What is an NLP text corpus? An NLP corpus (plural: “corpora”) is a collection of text organised into datasets. Corpora can be comprised of newspapers, novels, social media, transcripts of interviews or television shows, or other authentic text. An NLP corpus is useful for corpus linguistics, computational linguistics, and natural language processing research. A corpus could be raw text as originally spoken or written, or it could include annotations (annotated for parts of speech, such as nouns, verbs, and adjectives, or annotated by topic).