Machine Learning - Bias, data privacy, personalisation & digital airports

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Details

Machine learning - everyone's talking about it. We hear and read about various use cases for it, about ethics, bias and discrimination challenges, as well as the data itself.
We have found a group of wonderful speakers who will be sharing some of their work addressing these topics.

There are a limited number of spots available so please use the RSVP button responsibly so that you and other community members can enjoy this event.
We kindly ask everyone to follow our code of conduct (http://berlincodeofconduct.org/), and to provide their name (first and last) in order to be able to receive the badge and enter the venue.

★ AGENDA ★

• 18:45 – 19:15 Arrival Time (Food & Drinks)
• 19:15 – 19:30 Welcome Words
• 19:30 – 20:10 "Bias in Machine Learning: causes, effects and solutions" by Agnes van Belle & Hagop Boghazdeklian
• 20:15 – 20:45 "Data Privacy meets personalisation: Running machine learning on smartphones" by Sophie Chauvin
• 21:00 – 21:30 "Building the digital airport: solving transportation problems using cloud ecosystems and APIs" by Tyler Ayers
• 21:30 – 22:00 Networking, Food & Drinks

★ THE SPEAKERS ★
★ Agnes van Belle ★
Agnes is a Data Scientist at OLX Group for both the Search and Experimentation teams, focusing on improving the experience and fairness of consumer product buying and selling, and A/B tests. Formerly, she worked as Search R&D team lead at Textkernel, an Amsterdam-based company that makes software for the HR industry to automatically match people with jobs by parsing and ranking CVs and vacancies. Agnes studied Artificial Intelligence at the University of Amsterdam, and has been a panel member at Berlin Buzzwords, ECIR, ECML-PKDD, and Haystack Europe. Her main interests are around information retrieval and NLP.

★ Hagop Boghazdeklian ★
Hagop Boghazdeklian is a Data Scientist at OLX Group, where he focuses on Trust and Safety related projects, such as ad and chat moderation. Hagop studied Data Science and Econometrics at the Aix-Marseille University in France. He's passionate about Deep Learning applied to image processing and NLP.

★ Sophie Chauvin ★
Sophie used to be a researcher in physics before joining the thrilling world of tech. She worked for 2 years in a cybersecurity start-up in Paris, where she launched the data-science team. She moved to Berlin in April, to join Mobimeo. She is now applying machine learning to the field of urban mobility. She is particularly excited about designing ML-based solutions for real-world problems, and thinking about data strategy, research risk mitigation, productionizing prototypes and, of course, about helping reduce the carbon footprint of urban travellers.

★ Tyler Ayers ★
Tyler Ayers is a software architect and developer at Google working with customers on their Goggle Cloud projects, specifically on their API programs using Apigee API Management, and on app modernization, ecosystem, and hybrid cloud projects. He enjoys building web and mobile apps that hep people gain access to more qualified and trustworthy information online.

★ ABOUT WTM BERLIN ★

At Women Techmakers Berlin we have been encouraging diversity in tech in Berlin since 2015. We strive for visibility, networking and resources to make the tech community of Berlin inclusive. We are one of the most active chapters of the global Women Techmakers program run by Google.

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