Joint meetup with Women in Machine Learning and Data Science and Duchess France

Important Note: If you wish to come on-site sign up at meetup of Paris WiMLDS
Sign up here if you wish to attend remotely.

Details:
Hope you all had great summer and you are ready for our next exciting event. This time we are joining forces with The Women in Machine Learning & Data Science (WiMLDS) Meetup and Duchess France.

Schedule
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19:00 – Introduction by Duchess France, PyLadies Paris & the Paris WiMLDS teams
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19:15 – “Machine Learning in the Travel Industry: Tales and legends" by Begoña Ascaso, Principal Data Scientist at Egencia, an Expedia company
Abstract: The usage of Machine Learning has started a revolution in the last few years with the shift from university rooms to industrial prototypes. The travel industry has highly benefited from Machine Learning as the applicable business cases bloom in every single interaction with the customers or suppliers. In this talk, I'll just go through a few examples of these use cases at Egencia and extract learnings and conclusions.
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19:45 – “Transformers for multimodal electronical health records” by Ndèye Maguette Mbaye, Research Engineer at Institut Curie
Abstract: Interest has increased in the use of prognosis factors as a cursor for breast cancer personalized treatment. For clinicians, early detection of those factors can be helpful for a good management of the disease and for the choice of an efficient treatment. Moreover, it exists a huge amount of meaningful information in pathological reports, biological measurements and clinical information in a patient journey that remain unexploited. In that context, I propose to develop and apply novel machine learning techniques to predict cancer outcome such as recurrence or survival from multi-modal breast cancer patient data (including medical notes in natural languages and the outcome of various lab analyses). For that, I use a deep neural sequence transduction for electronic health records called BEHRT1. This model is inspired from one of the most powerful transformer-based architecture in Natural Language Processing: BERT2.
Twitter: @NdMaguetteMb
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20:15 – “Formal modeling of biological cyclic behavior with control points: the case of the cell cycle” by Deborah Boyenval, PhD Student at Université Côté d'Azur
Abstract: The main limitation of biologists rooted in an experimental practice is the ability to perform rigorous proofs in the absence of a language for formalizing the biological knowledge extracted from their experiments.
Biologists have identified numerous biochemical and genetic mechanisms involved in physiological functions or diseases, but once this knowledge is linked together it remains extremely difficult and expensive to predict the impact of genetic mechanisms on physiological functions.
Déborah will present to us her thesis, which focuses firstly on a reasonable mathematical specification of complex biological functions such as cell cycle checkpoints, which represent the main barrier against cancer. Secondly, she focused on the development of an automated proof method, using the mentioned tools, proving whether a set of genetic regulations is sufficient to generate cell cycle checkpoints.
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During the event, you can share content using @PyLadiesParis, @duchessfr & @WiMLDS_Paris

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Codes of Conduct
Duchess France, PyLadies and WiMLDS are dedicated to providing a harassment-free experience for everyone. We do not tolerate harassment of participants in any form. All communication should be appropriate for a professional audience including people of many different backgrounds.
Be kind to others. Do not insult or put down others. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate.
All attendees should read the full Code of Conduct before participating: https://github.com/WiMLDS/starter-kit/wiki/Code-of-conduct
Duchess code of conduct: https://github.com/DuchessFrance/duchessfr/blob/master/CODE_OF_CONDUCT.md
PyLadies Code of Conduct: https://github.com/PyLadiesParis/Codeofconduct