Name: 18. Hors-série #4 - Paris WiMLDS
Start: 2019-07-25T19:00:00+02:00
End: 2019-07-25T22:00:00+02:00
Location: Heetch - siège social

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 18th edition!

All genders may attend our meetups.
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Agenda

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

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19:25 – “Using weak supervision and transfer learning techniques to build knowledge graph to improve student experiences at Chegg” by Sanghamitra Deb, Staff Data Scientist @Chegg

Abstract: With 2.2 million subscribers and two hundred million content views, Chegg is a centralized hub where students come to get help with writing, science, math, and other educational needs. In order to impact a student’s learning capabilities, we present personalized content to students. Student needs are unique based on their learning style , studying environment and many other factors. Most students will engage with a subset of the products and contents available at Chegg.

Twitter: @sangha_deb

19:45 – “High performance language detection of Web pages" by Cécile Chailloux, Semantic Engineer @Dashlane

Abstract : Language detection is a classical issue in NLP, and there’s been plenty of methods and APIs appearing in the past years. But with millions of web pages to analyze daily, and a constant privacy concern, we went for an ad hoc solution at Dashlane. In this talk I will present you the various challenges and solutions we encountered doing so.

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20:10 – Panel discussion: Everything You Always Wanted to Know About Twitter (But Were Afraid to Ask)

The panel discussion will be moderated by Natalie Cernecka, WiMLDS Paris Co-Organizer

Panel participants :
Mathilde Kurzawa, Tech Recruiter @Heetch
Bio: After recruiting for the tourism industry, I started tech recruitment two years ago. I am particularly interested in the topics of diversity and inclusion, especially in the tech environment. I aim at creating safe spaces for everyone to express their talent and individuality, regardless of gender, race or age :) My motto : be good, and have fun !

Caroline Chavier, WiMLDS Paris Co-Founder
Bio: Highly involved in promoting diversity in engineering teams, Caroline is the co-founder of the Paris Women in Machine Learning & Data Science meet-up. In 2019, she will be an Inclusion & Diversity co-chairwoman at the RecSys Conference in Copenhagen. Caroline has always been passionate about encouraging women to network, speak at conferences and present their work to peers. She is also a passionate tech recruiter, always ready to tweet!

Marie Langé, Co-founder & CEO chez AMASAI
Bio: Marie had been working for more than 10 years on digital & e-commerce projects for international brands, before a career change in Data Science. With two other women, she has now created her own company, AMASAI, which aims at providing consulting to companies to help them succeed with Data and AI projects, with ethics stakes in mind.
Marie's been tweetting since 2008, at a time when she was an influential blogger and when Twitter was the place to be to grow an audience. It's still true today, and AMASAI uses extensively Twitter to gain visibility and legitimacy.

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 :

Twitter - https://twitter.com/HeetchEng
Medium - https://eng.heetch.com/

The room can welcome 80 people.
Please make sure to be on time. We can’t guarantee a seat once the meetup will have started.

Good news: the meetup will be filmed so if you can’t make it, you will find it on our Youtube channel: https://www.youtube.com/channel/UCLOS2KYfz8Yvt05hXUZEeVQ Hence, only subscribe if you plan to be with us!

Caroline Chavier

Chloe

Marina

ncernecka

Paris Women in Machine Learning & Data Science

Technology

Data Science

Data Mining

Machine Learning

Big Data

Open Source

Women in Technology

Data Management

Professional Women

Data Analytics

Data Visualization

Predictive Analytics

Artificial Intelligence

WiMLDS