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Put AI to work
8-9 Oct 2018: Training
9-11 Oct 2018: Tutorials & Conference
London, UK

Natural language processing, understanding, and generation

Amy Heineike (Primer)
14:35–15:15 Thursday, 11 October 2018
Models and Methods
Location: King's Suite - Balmoral
Secondary topics:  Financial Services, Media, Marketing, Advertising, Text, Language, and Speech
Average rating: ***..
(3.67, 3 ratings)

Who is this presentation for?

  • Data scientists, engineers, and product managers

Prerequisite knowledge

  • Familiarity with natural language processing concepts and terminology

What you'll learn

  • Understand the different types of algorithms in the NLP space and what to consider when building NLP applications


Natural language processing (NLP) is a common catch-all bucket for the world of natural language algorithms. As adoption of NLP technology continues to grow, it’s critical that builders of NLP applications understand the range of algorithms required to turn text into value.

Amy Heineike explains how she orchestrates natural language processing, understanding, and generation algorithms to build text-based AI applications for Fortune 500 companies. You’ll explore a variety of cutting-edge natural language processing, understanding, and generation algorithms and research, from text parsing, entity extraction, and organization extraction to sentiment analysis, event detection, and summarization, and learn how these new and old techniques are being used for AI applications. You’ll leave with a holistic understanding of different algorithms that power NLP applications and a better sense of what algorithms are best for the right job.

Photo of Amy Heineike

Amy Heineike


Amy Heineike is the vice president of product engineering at Primer, where she leads teams to build machines that read and write text leveraging natural language processing (NLP), natural language generation (NLG_, and a host of other algorithms to augment human analysts. Previously, she built out technology for visualizing large document sets as network maps at Quid. A Cambridge mathematician who previously worked in London modeling cities, Amy is fascinated by complex human systems and the algorithms and data that help us understand them.

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8/10/2018 8:43 BST

We see that NLP solutions claim to support different natural languages, like german, french, chineze. How relevant is this language support and how can you test if the support claim is valid ?