We are pleased to announce the following event, sponsored by Booking.com and in collaboration with Gemleb. In this session, people from Booking.com will explain us what kind of problems they deal with related to data science and machine learning (the talks may be more technical oriented than usual).
1) Data Science: For Fun and For Profit
Data Science is relatively new, but the ideas and techniques that form the underpinnings for this evidence-oriented discipline have a solid foundation in hundreds of years of scientific development. In order to understand the new science of data, one must first understand the science of science.
The Scientific Method, the unintended effects of repeated significance testing and Simpson’s paradox: this talk will focus on the practical applications of the theoretical constructs that lie at the heart of Data Science; and expand on some potential pitfalls of statistical analysis that you are likely to encounter when venturing into the field.
Bio: Lukas Vermeer (Data Scientist, Booking.com@lukasvermeer)
Lukas is an experienced data science professional with a background in computing science and online machine learning for real time decision support. A strong advocate of “Evidence-Based Everything”, he is forever learning and helping machines do the same. As a Data Scientist at Booking.com, the world’s leading accommodation website, Lukas is exploring novel ways to make booking hotels online into a more personal experience.
2) Topic Modelling on Travel Data.
Booking.com collects millions of diverse endorsements from its users, for example, London endorsed for Shopping, Brussels for Chocolate, Athens for Museums and Barcelona for its nightlife. These endorsements are organised using Latent Dirichlet Allocation to a set of topics and used to personalise the Email-Marketing campaign of Booking.com. The results from experiments on more than 40 million unique users demonstrate the conceptual value of the discovered topics.
Bio: Athanasios Noulas
Athanasios Noulas completed his PhD in Machine Learning in the University of Amsterdam where he focused on Dynamic Bayesian Networks and Deep Learning. He then worked as a strategist in Source Capital where he developed algorithms for high frequency automated training. He is currently working for Booking.com as a Data Scientist in the Visitor Profiling team, where he performs analysis on user-behaviour and implements algorithms that adjust the web-site to the user’s needs.
At the end we will have some drinks and time for networking.
If you want to attend, please register via meetup.