#17 Paris Women in Machine Learning & Data Science: Image Editing, Classical Music, & Leadership
Before we started, we shared highlights from the previous months:
🔨 The WiMLDS global team is organizing Scikit Learn sprints in 3 locations: Nairobi (22nd of June), New-York (25th of August) & San Francisco (2nd of November). Spread the word!
🎀 On the 21st of May 2019, Caroline Chavier & Chloé-Agathe Azencott introduced the basics of machine learning & presented WiMLDS to students at the Women in Science conference in honour of Nicole El Karoui.
We believe it is crucial to have visible diverse role models in machine learning and data science, that’s why we always happy to showcase the first time speakers. Many times, we had the privilege to listen to the exclusive presentations created specifically for our events, and this meetup was no exception!
🎬 We got lucky > the meetup was filmed! 🥁
The night started with a presentation by Camille Couprie, Facebook AI Researcher in the Paris office, who talked about “Image generative modeling for design inspiration and image editing”.
Generative models, and in particular adversarial ones, are becoming prevalent in computer vision as they enhance artistic creation, inspire designers, prove useful in semi-supervised learning or robotics applications. Camille explained how to develop the abilities of Generative Adversarial Networks (GANs) to deviate from training examples to generate original images of fashion designs. Since GANs’ limitation is production of low resolution raw images, Camille presented solutions to produce vectorized results, and showed how the developed method may be useful for image editing. Check out the code ⬆️ and slides here ⬇️
🎼 After Camille, Victoire Louis, Data Scientist at Edelia, took the stage to make the audience observe an orchestra conductor’s movements!
Victoire’s presentation was about “How to marry tech & classical music: prediction of a conductor’s hand gestures with recurrent neural networks”.
🎯 She explained how she ended up doing a research on recurrent neural networks, and introduced her project, the role of a music conductor, and her dataset. She presented how she discovered coding in R and Python and why coding was just a way to achieve her goal. Finally, she talked about how she had answered her research questions and about different models she had tried.
We hope to see you at our next meetup, on the 25th of July at Heetch!
If you want to keep posted about our activities, you are welcome to
📑check our Google spreadsheet if you want to speak 📣, host 💙, or help 🌠
📍join our Slack channel for more discussions about machine learning, data science, and diversity in tech!
📩send an email to the Paris WiMLDS team to keep in touch >firstname.lastname@example.org
🔥 Feel free to share your company or lab’s job positions for free on WiMLDS’ website.