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The Power of Time Series for Renewable Energies

With Rosana de Oliveira Gomes

Renewable energies are a hot topic in times of extreme climate consequences. In this talk, I’ll explore the topic of time series through the use case of modeling energy supply and demand in Brazil. Most of thr energy in

DN22 •
Data Science

Argumentation Mining – A bridge between Philosophy and NLP

With Mohammad Yeghaneh

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DN22 •
Data Science

Against Dark Patterns – From Deceptive Design to Trust

With Ame Elliot

Learn about emerging trends in combatting deceptive design (formerly known as dark patterns) based on a series of global multi-stakeholder workshops from the World Wide Web Foundation’s Tech Policy Design Lab. Learning from leaders from over 20 countries, we

DN22 •
Data Science

Building an explainable recommender system

With Benjamin Kempinski

“Recommendation systems became in integral part of our online shopping and content consumption. With cloud services and techniques like deep learning it has become dead-simple to fit a model to your data and have a black box model. However,

DN22 •
Data Science

Applied Data Incubator Panel: Why is NLP the future of AI?

With Barak Shalom

, Jakub Bares

, Daniel Pavlicek

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DN22 •
Data Science

How biased is our knowledge of the world and why?

With Franziska Heine

Franziska’s keynote “How biased is our knowledge of the world and why? looks at data bias in open data environments. Specifically, Franziska explains how Wikipedia and Wikidata address this challenge and how possible solutions can look like. Want priority

DN22 •
Data Science

Running AB tests at scale

With Jakob Graff

When does it make sense to invest in AB testing and how can an organisation effectively scale AB testing? This talk introduces a holistic framework for testing at scale and highlights best practices and pitfalls. The talk is relevant

DN22 •
Data Science

Quantum computer & data processing – disruptive or destructive

With William Hurley (Whurley)

, Matyas Kovacs

, Shahar Graf

The invention of the capable quantum computer promises to undermine how we work with data. Processing unbelievably large amounts of data very quickly would change how the world works. But not necessarily in a good way. Some scientists are

DN22 •
Data Science

Live build of a Python service that tracks, transforms and delivers heart rate data in real time using open source components

With Javier Blanco Cordero

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DN22 •
Data Science

Scalable and sustainable AI

With Danko Nikolic

Deep learning does no scale very well. I will explain where the problem is and why we cannot do it other way but build ever larger models. This makes our AI growth unsustainable. I will describe several approaches for

DN22 •
Data Science