📌 IMPORTANT NOTE: REGISTRATION FOR THIS EVENT 📌
The event will be held at the Google office, Shibuya Stream. For security reasons related to entering the office areas of Shibuya Stream, kindly fill out this form to register for the event. (You cannot enter the office building without registration.) https://forms.gle/px5dYNDwBSjNH1i48
MLT "Women in Machine Learning" in collaboration with Google Japan is part of our Diversity and Inclusion efforts. This event aims to inform, support and empower women considering a career in Machine Learning, Data Science and related fields. We'd like to primarily invite women to be part of this event, but welcome all people, regardless of gender or background.
📌 EVENT SCHEDULE 📌
● 13:15 Doors open – Reception | Registration
● 14:00-14:15 Welcome note, Suzana Ilic (Machine Learning Tokyo)
● 14:15-14:45 "FactoryFactories and so can you – OO design patterns for machine learning", Chris Gerpheide, CTO Bespoke Inc.
● 14:45-15:15 "Detecting word meaning change – from probabilistic models to BERT", Syrielle Montariol, PhD Student National Institute of Informatics, Tokyo | LIMSI - CNRS, Université Paris-Saclay, Paris Société Générale, Paris
● 15:15-15:30 Short break and networking
● 15:30-16:45 Panel discussion and Q&A
● 16:45-17:45 Networking with finger food & drinks
● 18:00 Closing
📌 TALKS & SPEAKER DETAILS 📌
🤖"FactoryFactories and so can you – OO design patterns for machine learning", Chris Gerpheide, CTO Bespoke Inc.
💻Object-oriented programming has long been known for its design patterns. In this talk, Chris will describe a number of design patterns that are particularly useful for machine learning applications, including why and how you can implement them yourself.
Chris Gerpheide is the CTO at Bespoke Inc. https://www.be-spoke.io
Before joining Bespoke, she was engineering manager at Amazon Web Services. In her free time, she enjoys learning Japanese, hiking, and teaching children programming.
🤖 "Detecting word meaning change – from probabilistic models to BERT", Syrielle Montariol, PhD Student
💻Word usage, meaning and connotation change throughout time, mirroring the cultural and technological evolution of society. Diachronic word embeddings are used to grasp these changes in an unsupervised way. It is useful for social and linguistic research, by detecting and interpreting the causes of semantic shifts, but also for many NLP tasks to study temporal corpora. Syrielle will introduce methods to detect word meaning change, from models relying on classical word embeddings to the revolution of contextualised embeddings.
Syrielle Montariol received a Master's degree in Statistics from a French engineering school and started her PhD in 2018 in Paris, working in parallel at Université Paris-Saclay and at the company Société Générale. Her research goal is to use semantic change as a tool to detect and understand social and political crisis.
💙 –– THANK YOU ––
A huge THANK YOU goes out to Google Japan for hosting this event at their new office in Shibuya Stream and for sponsoring food and drinks for the networking session.
Thank you to Women Techmakers – Google's Women Techmakers program provides visibility, community, and resources for women in technology. https://www.womentechmakers.com/
📌 –– MLT PATRON ––
Always on the waiting list for MLT events? Become a MLT Patron and get early access to workshops, study groups and talks. https://www.patreon.com/MLTOKYO
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MLT events are for community building and knowledge sharing. We politely ask that company representatives, recruiters and consultants looking to hire or sell their services do not come to this event.
–– CODE OF CONDUCT ––
MLT promotes an inclusive environment that values integrity, openness and respect. https://github.com/Machine-Learning-Tokyo/MLT_starterkit