PyData Hamburg 2018.6 - Data Models from Theory to Production

PyData Hamburg
PyData Hamburg
Public group
Location image of event venue


Hi Folks,

For our June PyData meetup, we will focus on building data products in Python as well as the long way to production. Our guest speaker is Philipp Kähler, who currently works as Data Science Engineer at mytaxi. Our second speaker is Daniel Kohlsdorf, Data Scientist at Xing AG.

We are looking forward to seeing all.

The PyData Hamburg Crew.


# Introduction & Announcements**

# Feature Talk: Data products at mytaxi - from research to production.

Abstract: The talk describes how we develop a taxi fare estimation service at mytaxi. It starts with the conceptional phase and focuses then on the implementation. You will learn how we build the tech stack, tried different architectures and finally shipped a service to production....

Bio: Philipp did his Master in Informatics at FH Wedel while working as a Data Engineer at mytaxi. Now he works as a Data Science Engineer where he develops and deploys models in production.

# Second Talk: A Deep Dive Into Gradient Boosting

Gradient Boosted Decision Trees are a price winning machine learning model that can be used for classification, prediction and ranking tasks. This talk will give a theoretical introduction to Decision Trees and Gradient Boosting and give examples from practical applications.

Bio: Daniel is a Data Scientist at Xing where he builds machine learning models for recommendation systems. He got his PhD in Computer Science with a specialisation in intelligent Systems from the Georgia Institute of Technology.

Event will be hosted by mytaxi and snacks and drinks will be provided.