14. Women in Machine Learning & Data Science in Paris

This is a past event

200 people went

Location image of event venue

Details

The Women in Machine Learning & Data Science (WiMLDS) Meetup aims to inspire, educate, regardless of gender, and support women and gender minorities in the field. We are back for our 14th edition!

All genders may attend our meetups.
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Agenda

19:00 – Introduction by Malt & the Paris WiMLDS team

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19:25 – “Machine Learning for automatic diagnosis: why your deep neural network might not work” by Manon Ansart, PhD Student @AramisLab (Sorbonne Université, Inserm, ICM, CNRS, Inria)

Abstract: The early diagnosis of neurodegenerative diseases is crucial, as it could lead to early treatment and better chances of stopping the process. Machine learning algorithms provide an opportunity to diagnose these diseases earlier through automatic diagnosis, but their application to the medical domain is not straightforward. From data set size to interpretability, we will see why the beautiful, trendy and complex solution we can first think about might not be the best one.

Twitter: @AnsartManon

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19:45 – “Predicting with GCP (Google Cloud Platform)" by Giulia Bianchi, Data Scientist @Xebia

Abstract : With the release of Google Cloud AutoML, Google Cloud Platform provides yet another out-of-the-box AI managed service. But this doesn’t mean that data scientists have no say in training and deploying customised machine learning models in the cloud. There are services, such as Cloud ML Engine, devoted to this specific goal. Let’s see how a data scientist can exploit GCP potential to expose its own model.

Twitter: @Giuliabianchl

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///// WE ARE SORRY TO INFORM YOU THAT THE TALK GOT CANCELLED > It will be replaced by an interactive session /////

20:10 – "What's the point of having nerds in newsrooms (except for fixing the printer)?", by Laura Motet, Data Journalist at Le Monde

Abstract: Data-journalists are usually compared to unicorns. Rare, since they know their ways around computers, but also a bit mysterious, since not many know exactly what they can really be used for. How does their work differ from other technical jobs in the newsroom, like graphics designer or programmer? Are they working along side "traditional" journalists? Do they use machine learning? What are the clichés and truths of being a data-journalist?

Twitter: @LaMotet

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20:45 – Networking / Cocktail

During the event, you can share content using #WiMLDSParis & @WiMLDS_Paris

After the meet-up, all the slides will be available on our Medium page : https://medium.com/@WiMLDS_Paris

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Host information :

The room can welcome 90 people.
Please make sure to be on time. We can’t guarantee a seat once the meetup will have started.

Twitter - https://twitter.com/malt_fr
Website: https://www.malt.fr/