Online Meetup: Active Learning for NLP

Hi everyone!

We hope you're doing well. In collaboration with Sydney NLP, we are proud to present our next event - on active learning in NLP with Rob Munro.

I was lucky to meet Rob in San Francisco at his meetup. His has deep understanding of not only linguistics, NLP, AI, but also many insights into how to build great products and how to succeed as a startup. He is also a kind, friendly and thoughtful person.

He is originally from Australia, and has kindly agreed to repeat his latest talk in a friendly time zone for his fellow NLP enthusiasts Down under. My colleagues had to wake up at 5am to attend his talk and it was so good that they'll dial in again for this one! So, please don't miss out this talk, spaces are limited.

HOW TO SIGN UP

Please register with Zoom at
https://us02web.zoom.us/webinar/register/WN_QptItzbLS-2vUvYc61SWwQ

The meeting password will be emailed on the day of the event.

If you're interested in asking a question, there will be a forum available during the event for that in the Zoom call - we'll see any questions you post. The password to the Zoom event will be sent on the day of the event itself, look forward to seeing you there!

THE TALK INFO

Robert Munro: Active Learning for Natural Language Processing

More than 90% of machine learning applications improve with human feedback. For example, a model that classifying news articles into pre-defined topics has been trained on 1000s of examples where humans have manually annotated the topics. However, if there are tens of millions of news articles, it might not be feasible to manually annotate even 1% of them. If we only sample randomly, we will mostly get popular topics like "politics" that the machine learning model can already identify accurately. So, we need to be smarter about how we sample. This talk is about "Active Learning", the process of deciding what raw data is the most optimal for human review, covering: Uncertainty Sampling; Diversity Sampling; and some advanced methods like Active Transfer Learning.

BIO
Robert Munro has worked as a leader at several Silicon Valley machine learning companies and also led AWS's first Natural Language Processing and Machine Translation solutions. Robert is the author of Human-in-the-Loop Machine Learning, covering practical methods for Active Learning, Transfer Learning, and Annotation. Robert organizes Bay Area NLP, the world's largest community of Language Technology professionals. Robert is also a disaster responder and is currently helping with the response to COVID-19.