Data Science Meetup Hamburg

=== Online Meeting via Hangout starts at 18:30 ===

=== Introduction ===

Short intro by Marc Päpper

=== Talk 1 ===

Dennis Kraft, Software Engineer at Google on "Differential Privacy at Google and the COVID-19 Community Mobility Reports"

This talk will give an introduction to differential privacy (DP) and its practical use cases.
After a brief review of existing anonymization strategies, the high level concepts of DP will be explained, followed by a more detailed look at the benefits and challenges of DP and Google's open source DP libraries.
The talk concludes with a real world example of DP at Google based on the COVID-19 Community Mobility Reports. The reports provide insight into how social distancing policies affect mobility patterns and illustrate how DP can be used to extract valuable statistical information while protecting user privacy at the same time.

Dennis is a Software Engineer at Google and member of the Anonymization team. His main focus is on building and testing fundamental differential privacy tools.

=== Short Break ===

=== Talk 2 ===

Moritz Meister, Software Engineer at Logical Clocks AB on "MLOps with a Feature Store: Filling the Gap in ML Infrastructure"

MLOps is a trend in machine learning (ML) engineering that unifies ML system development (Dev) and ML system operation (Ops). Some ML lifecycle frameworks, such as TensorFlow Extended, are based around end-to-end pipelines that start with raw data and end in production models. During this talk we will introduce the concept of a feature store as the missing piece of ML infrastructure that enables faster lower cost deployment of models. We will show how the Hopsworks Feature Store - factors monolithic end-to-end ML pipelines into feature and model training pipelines that can each run at different cadences. We will show examples of ingestion and training pipelines including hyperparameter optimization and model deployment.

Moritz has a background in Econometrics and holds MSc degrees in Computer Science from Politecnico di Milano and Universidad Politecnica de Madrid. He has previously worked as a Data Scientist on projects for Deutsche Telekom and Deutsche Lufthansa in Germany, helping them to productionize machine learning models to improve customer relationship management.