Hervé Schnegg

The Telegraph

Talk Abstract: How to evaluate recommender systems?

Recommender systems allow us to build personalised experience for our users. But do we know how to evaluate them?

Bio: Principal Data Scientist at The Telegraph. Interested in data mining, machine learning and predictive analytics. Developed news recommender systems, churn models and various propensity models. Uses R for data analysis, Python for product prototyping and Clojure for side projects.

Wednesday April 10th , 2019
Auditorium
6:15 pm-
9:00 pm
DSF Day 3 - Data Science in Media hosted by Facebook Join Data Science Festival London, in partnership with Facebook this April. The evening will consist of 4 lightning talks and a panel discussion on how Data Science is impacting media and online content industry. Please click here to apply…
Sector: