[webWorkshop] Text Summarization & Explainability with Reuters News Data

NLP Zurich is organizing a hands-on workshop on text summarization and explainability 28th November 2020. Places are limited. If you need to cancel, please do it 3-4 days ahead so that someone could take your place. Thank you!

Instructors: Nina Hristozova, Nadja Herger and Andreea Iuga from Thomson Reuters Labs

Prerequisites (please read the workshop description to see if this training is for you or not):
• Python knowledge - Good
• Understanding deep learning concepts - Good
• Knowledge of NLP - Beginner
• Google Colab set up

Agenda

9:45 Join the workshop & access checks
10:00 Deep Learning-Driven Text Summarization & Explainability with Reuters News Data Workshop
12:00 Virtual Hugs and Kisses ⊂(◉‿◉)つ

Workshop description:

This advanced Natural Language Processing (NLP) workshop is focused on text summarization and allows you to automatically generate news headlines powered by Reuters News. Moreover, you will get a glimpse into the emerging field of Explainable AI.

In this workshop, we focus on text summarization, as it is not commonly showcased in tutorials despite being a powerful and challenging application of NLP.

We see a trend towards pre-training Deep Learning models on a large text corpus and fine-tuning them for a specific downstream task (also known as transfer learning). In this hands-on workshop, you will get the opportunity to apply a state-of-the-art summarization model to generate news headlines. We fine tuned this model on Reuters news data, which is professionally produced by journalists and strictly follows rules of integrity, independence and freedom from bias.

The move towards more complex models for NLP tasks makes the need for AI explainability more apparent. How can we increase trust in what the model generated? With this workshop, we will bring you a step closer to answering this question.

The Python programming language will be used as it has a huge community across various industries and has become a standard in applied NLP. We chose Google Colab to host our code and training material to avoid any technical challenges.

The introduced NLP topics around text summarization and explainable AI are strengthened through guided hands-on exercises, supervised by mentors with several years of industry experience. At the end of this session, you will walk away with an interactive notebook to get a head start in applying the learned concepts to your own challenges.

Sneak peek: https://tinyurl.com/y4dxuao7

The instructors:

Nina Hristozova
LinkedIn: https://linkedin.com/in/nina-hristozova-80245baa
Nina Hristozova is a Data Scientist at TR Labs. She has a BSc in Computer Science from the University of Glasgow, Scotland. As part of her role at the Labs she has worked on a wide range of projects applying Machine Learning and Deep Learning to a variety of NLP problems. Her current focus is on applied summarization with Transfer Learning. Outside of work she is a Co-organizer of the NLP Zurich Meetup to spread the love and knowledge for NLP and plays & coaches volleyball in Zug.

Nadja Herger
Nadja Herger is a Data Scientist at TR Labs, based in Switzerland. She is primarily focusing on Deep Learning PoCs within the Labs, where she is working on applied NLP projects in the legal and news domains, applying her skills to text classification, metadata extraction, and summarization tasks. Before joining Thomson Reuters, she obtained her Ph.D. in Climate Science from the University of New South Wales, Australia. She has successfully made the transition from working with Spatio-temporal data to working with text-based data on the job. Nadja is passionate about education, which is reflected in her ongoing mentorship of students within TR, as well as South African students from previously disadvantaged groups who are aspiring to get into Data Science.

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